https://sustainabilitymethods.org/index.php?title=Wordcloud&feed=atom&action=historyWordcloud - Revision history2024-03-29T14:40:26ZRevision history for this page on the wikiMediaWiki 1.33.0https://sustainabilitymethods.org/index.php?title=Wordcloud&diff=6579&oldid=prevOllie at 07:45, 21 March 20222022-03-21T07:45:28Z<p></p>
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<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>'''Note:''' This entry revolves specifically around Wordclouds. For more general information on quantitative data visualisation, please refer to [[Introduction to statistical figures]]. For more info on Data distributions, please refer to the entry on [[Data distribution]].</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>'''Note:''' This entry revolves specifically around Wordclouds. For more general information on quantitative data visualisation, please refer to [[Introduction to statistical figures]]. For more info on Data distributions, please refer to the entry on [[Data distribution<ins class="diffchange diffchange-inline">]]. Another example of a worldcloud can be found in this [[Price_Determinants_of_Airbnb_Accommodations#Wordcloud|entry</ins>]].</div></td></tr>
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</table>Olliehttps://sustainabilitymethods.org/index.php?title=Wordcloud&diff=5998&oldid=prevChristopher Franz: /* R Code */2021-07-06T09:35:11Z<p><span dir="auto"><span class="autocomment">R Code</span></span></p>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># For comparison we can also look at the inaugural speech of US President Joe Biden from 2021</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># For comparison we can also look at the inaugural speech of US President Joe Biden from 2021</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Biden = readLines("/PresidentUS.txt", encoding = "UTF-8") </div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Biden = readLines("/PresidentUS.txt", encoding = "UTF-8") </div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>df_biden = nube(Biden)</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>df_biden = nube(Biden)</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>[[File:PutinSpeech.png|500px|thumb|left|Fig.2: Wordcloud of the most used words during Vladimir Putin's inauguration speech in 2016]]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>[[File:PutinSpeech.png|500px|thumb|left|Fig.2: <ins class="diffchange diffchange-inline">'''</ins>Wordcloud of the most used words during Vladimir Putin's inauguration speech in 2016<ins class="diffchange diffchange-inline">'''</ins>]]</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>[[File:BidenSpeech.png|500px|thumb|center|Fig.3: Wordcloud of the most used words during Joe Biden's inauguration speech in 2021]]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>[[File:BidenSpeech.png|500px|thumb|center|Fig.3: <ins class="diffchange diffchange-inline">'''</ins>Wordcloud of the most used words during Joe Biden's inauguration speech in 2021<ins class="diffchange diffchange-inline">'''</ins>]]</div></td></tr>
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</table>Christopher Franzhttps://sustainabilitymethods.org/index.php?title=Wordcloud&diff=5997&oldid=prevChristopher Franz: /* Definition */2021-07-06T09:34:04Z<p><span dir="auto"><span class="autocomment">Definition</span></span></p>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[File:HarryWordCloud.png|300px|thumb|right|'''A Wordcloud of the most commonly used words in the Harry Potter book series.''' Unfortunately, this gives little insight since the result of the visualisation is quite predictable. [https://public.tableau.com/app/profile/dave.andrade/viz/WordCloudsandWizardry/HarryPotterWordCloudDashboard Source]]]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[File:HarryWordCloud.png|300px|thumb|right|'''A Wordcloud of the most commonly used words in the Harry Potter book series.''' Unfortunately, this gives little insight since the result of the visualisation is quite predictable. [https://public.tableau.com/app/profile/dave.andrade/viz/WordCloudsandWizardry/HarryPotterWordCloudDashboard Source]]]</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Disadvantages'''</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Disadvantages'''</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* If your data set is not prepared and cleaned you might get little to no insight into the data. <del class="diffchange diffchange-inline">Besides</del>, <del class="diffchange diffchange-inline">it </del>is important to have a clear idea why this method is being applied and for which purposes. Otherwise the wordcloud will simply visualise evident or common words with no use for research.</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* If your data set is not prepared and cleaned you might get little to no insight into the data. <ins class="diffchange diffchange-inline">In this context</ins>, <ins class="diffchange diffchange-inline">"cleaning" refers to the deletion of double spaces, numbers, punctuation, fill words ("and", "or", "but", "is", "at" etc.) and shifting all words to lowercase, among other measures. </ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline">* It </ins>is important to have a clear idea why this method is being applied and for which purposes. Otherwise the wordcloud will simply visualise evident or common words with no use for research.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* A general disadvantage of wordclouds is caused by the so-called [https://www.data-to-viz.com/caveat/area_hard.html “area is a bad metaphor”] phenomenon. Human eyes can have difficulty visually identifying the size of an area, in this context, a word’s size compared to the other words around it. Analytical accuracy of such visualisations can be especially compromised if the words have different lengths: wordclouds tend to emphasise long words over short words as shorter words need less space and thus might appear smaller.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* A general disadvantage of wordclouds is caused by the so-called [https://www.data-to-viz.com/caveat/area_hard.html “area is a bad metaphor”] phenomenon. Human eyes can have difficulty visually identifying the size of an area, in this context, a word’s size compared to the other words around it. Analytical accuracy of such visualisations can be especially compromised if the words have different lengths: wordclouds tend to emphasise long words over short words as shorter words need less space and thus might appear smaller.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Wordclouds consider one word at a time. So, for example, if customers often describe the product they purchased as “not good” in their reviews, the wordcloud will be likely to visualise it as “not” and “good” separately. Taken into account that the words are allocated randomly in the cloud, this only further impairs an accurate analysis of the visualisation.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Wordclouds consider one word at a time. So, for example, if customers often describe the product they purchased as “not good” in their reviews, the wordcloud will be likely to visualise it as “not” and “good” separately. Taken into account that the words are allocated randomly in the cloud, this only further impairs an accurate analysis of the visualisation.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>All in all, wordclouds can be a good intro exercise when getting familiar with text mining and neural language processing. It offers a simple and comprehensible visualisation, however its features are quite limited if a thorough textual analysis is required. As an alternative, it might be better to use a [[Barplots,_Histograms_and_Boxplots#Barplots|barplot]] or [https://www.data-to-viz.com/graph/lollipop.html a lollipop chart], since they also make it possible to rank words by usage frequency. For example, you can easily allocate the tenth most common word in a barplot, whereas in a wordcloud you might struggle to see the difference in sizes after identifying the first 5 most commonly used terms.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>All in all, wordclouds can be a good intro exercise when getting familiar with text mining and neural language processing. It offers a simple and comprehensible visualisation, however its features are quite limited if a thorough textual analysis is required. As an alternative, it might be better to use a [[Barplots,_Histograms_and_Boxplots#Barplots|barplot]] or [https://www.data-to-viz.com/graph/lollipop.html a lollipop chart], since they also make it possible to rank words by usage frequency. For example, you can easily allocate the tenth most common word in a barplot, whereas in a wordcloud you might struggle to see the difference in sizes after identifying the first 5 most commonly used terms.</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"></del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== R Code ==</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== R Code ==</div></td></tr>
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</table>Christopher Franzhttps://sustainabilitymethods.org/index.php?title=Wordcloud&diff=5996&oldid=prevChristopher Franz at 09:31, 6 July 20212021-07-06T09:31:38Z<p></p>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Definition ==</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Definition ==</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>Wordcloud is a cluster of words or visualisation of the most commonly or frequently used terms within <del class="diffchange diffchange-inline">the analysed data set</del>. The basic principle is the higher the frequency, the more prominent the word <del class="diffchange diffchange-inline">on </del>the figure <del class="diffchange diffchange-inline">is</del>. Wordcloud is a relatively easy and quick text mining tool which allows to get a rough overview of the word usage within the dataset, which can give further ideas when studying <del class="diffchange diffchange-inline">correlations connected to </del>word usage frequency. Wordclouds can also help get first impression of the differences or similarities when working with two textual datasets.</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>Wordcloud is a cluster of words or visualisation of the most commonly or frequently used terms within <ins class="diffchange diffchange-inline">a given dataset of words</ins>. The basic principle is <ins class="diffchange diffchange-inline">that </ins>the higher the frequency, the more prominent the word <ins class="diffchange diffchange-inline">is in </ins>the figure. Wordcloud is a relatively easy and quick text<ins class="diffchange diffchange-inline">-</ins>mining tool which allows to get a rough overview of the word usage within the dataset, which can give further ideas when studying word usage frequency. Wordclouds can also help get first impression of the differences or similarities when working with two textual datasets.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Advantages'''</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Advantages'''</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* Due to their simple design, wordclouds rarely need additional explanation of the visualised results</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* Due to their simple design, wordclouds rarely need additional explanation of the visualised results<ins class="diffchange diffchange-inline">.</ins></div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* Straightforward and colourful figure can be often used for aesthetic purposes and in order to quickly get one’s point across</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* Straightforward and colourful figure can be often used for aesthetic purposes and in order to quickly get one’s point across<ins class="diffchange diffchange-inline">.</ins></div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>[[File:HarryWordCloud.png|300px|thumb|right|<del class="diffchange diffchange-inline">Fig.1: </del>Wordcloud of the most commonly used words in the Harry Potter book series gives little insight since the result of the visualisation is quite predictable. <del class="diffchange diffchange-inline">(</del>[https://public.tableau.com/app/profile/dave.andrade/viz/WordCloudsandWizardry/HarryPotterWordCloudDashboard Source]<del class="diffchange diffchange-inline">)</del>]]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>[[File:HarryWordCloud.png|300px|thumb|right|<ins class="diffchange diffchange-inline">'''A </ins>Wordcloud of the most commonly used words in the Harry Potter book series<ins class="diffchange diffchange-inline">.''' Unfortunately, this </ins>gives little insight since the result of the visualisation is quite predictable. [https://public.tableau.com/app/profile/dave.andrade/viz/WordCloudsandWizardry/HarryPotterWordCloudDashboard Source]]]</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Disadvantages'''</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Disadvantages'''</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* If your data set is not prepared and cleaned you might get little to no insight into the data. Besides, it is important to have a clear idea why this method is being applied and for which purposes. Otherwise the wordcloud will simply visualise evident or common words with no use for research <del class="diffchange diffchange-inline">(Fig.1)</del>.</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* If your data set is not prepared and cleaned you might get little to no insight into the data. Besides, it is important to have a clear idea why this method is being applied and for which purposes. Otherwise the wordcloud will simply visualise evident or common words with no use for research.</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* <del class="diffchange diffchange-inline">General </del>disadvantage of wordclouds is caused by the so-called [https://www.data-to-viz.com/caveat/area_hard.html “area is a bad metaphor”] phenomenon. Human eyes can have difficulty visually identifying the size of an area, in this context, a word’s size compared to the other words around it. Analytical accuracy of such visualisations can be especially compromised if the words have different lengths: wordclouds tend to emphasise long words over short words as shorter words need less space and thus might appear smaller.</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* <ins class="diffchange diffchange-inline">A general </ins>disadvantage of wordclouds is caused by the so-called [https://www.data-to-viz.com/caveat/area_hard.html “area is a bad metaphor”] phenomenon. Human eyes can have difficulty visually identifying the size of an area, in this context, a word’s size compared to the other words around it. Analytical accuracy of such visualisations can be especially compromised if the words have different lengths: wordclouds tend to emphasise long words over short words as shorter words need less space and thus might appear smaller.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Wordclouds consider one word at a time. So, for example, if customers often describe the product they purchased as “not good” in their reviews, the wordcloud will be likely to visualise it as “not” and “good” separately. Taken into account that the words are allocated randomly in the cloud, this only further impairs an accurate analysis of the visualisation.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Wordclouds consider one word at a time. So, for example, if customers often describe the product they purchased as “not good” in their reviews, the wordcloud will be likely to visualise it as “not” and “good” separately. Taken into account that the words are allocated randomly in the cloud, this only further impairs an accurate analysis of the visualisation.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>All in all, wordclouds can be a good <del class="diffchange diffchange-inline">for </del>intro exercise when getting familiar with text mining and neural language processing. It offers a simple and comprehensible visualisation, however its features are quite limited if a thorough textual analysis is required. As an alternative, it might be better to use a [[Barplots,_Histograms_and_Boxplots#Barplots|barplot]] or [https://www.data-to-viz.com/graph/lollipop.html a lollipop chart], since they also make it possible to rank words by usage frequency, <del class="diffchange diffchange-inline">i.e. </del>you can easily allocate the tenth most common word in a barplot, whereas in a wordcloud you might struggle to see the difference in sizes after identifying the first 5 most commonly used terms.</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>All in all, wordclouds can be a good intro exercise when getting familiar with text mining and neural language processing. It offers a simple and comprehensible visualisation, however its features are quite limited if a thorough textual analysis is required. As an alternative, it might be better to use a [[Barplots,_Histograms_and_Boxplots#Barplots|barplot]] or [https://www.data-to-viz.com/graph/lollipop.html a lollipop chart], since they also make it possible to rank words by usage frequency<ins class="diffchange diffchange-inline">. For example</ins>, you can easily allocate the tenth most common word in a barplot, whereas in a wordcloud you might struggle to see the difference in sizes after identifying the first 5 most commonly used terms.</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== R Code ==</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== R Code ==</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"></del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Let's try and create our own wordclouds. For the exercise we will use the transcripts of the inaugural speeches of the President of Russia ([http://en.kremlin.ru/events/president/news/57416 from 2016]) and the President of the USA ([https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/01/20/inaugural-address-by-president-joseph-r-biden-jr/ from 2021]). Creating two wordclouds can help us obtain a general understanding of which topics were in the centre of attention for the presidents during their speeches.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Let's try and create our own wordclouds. For the exercise we will use the transcripts of the inaugural speeches of the President of Russia ([http://en.kremlin.ru/events/president/news/57416 from 2016]) and the President of the USA ([https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/01/20/inaugural-address-by-president-joseph-r-biden-jr/ from 2021]). Creating two wordclouds can help us obtain a general understanding of which topics were in the centre of attention for the presidents during their speeches.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
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</table>Christopher Franzhttps://sustainabilitymethods.org/index.php?title=Wordcloud&diff=5978&oldid=prevOllie at 16:29, 5 July 20212021-07-05T16:29:28Z<p></p>
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 16:29, 5 July 2021</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l101" >Line 101:</td>
<td colspan="2" class="diff-lineno">Line 101:</td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[File:PutinSpeech.png|500px|thumb|left|Fig.2: Wordcloud of the most used words during Vladimir Putin's inauguration speech in 2016]]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[File:PutinSpeech.png|500px|thumb|left|Fig.2: Wordcloud of the most used words during Vladimir Putin's inauguration speech in 2016]]</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[File:BidenSpeech.png|500px|thumb|center|Fig.3: Wordcloud of the most used words during Joe Biden's inauguration speech in 2021]]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[File:BidenSpeech.png|500px|thumb|center|Fig.3: Wordcloud of the most used words during Joe Biden's inauguration speech in 2021]]</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><br></ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Above we see two wordclouds resulting from out text mining performed on the transcripts of Biden and Putin during their inauguration ceremonies. Based on the visualisations, we can conclude, that the most used word for both presidents were the names of their countries. Both presidents addressed the people by using different words, such as "people" and "citizens" in case of Vladimir Putin's speech, and "nation" and "Americans" in case of Biden's speech. Among other more prominent terms are such words as "democracy", "story", "war", "justice", "unity" and "work" used by the American president, and "challenges", "time", "history", "work", "towards", "fatherland", "achieve" and "life" used by the Russian president.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Above we see two wordclouds resulting from out text mining performed on the transcripts of Biden and Putin during their inauguration ceremonies. Based on the visualisations, we can conclude, that the most used word for both presidents were the names of their countries. Both presidents addressed the people by using different words, such as "people" and "citizens" in case of Vladimir Putin's speech, and "nation" and "Americans" in case of Biden's speech. Among other more prominent terms are such words as "democracy", "story", "war", "justice", "unity" and "work" used by the American president, and "challenges", "time", "history", "work", "towards", "fatherland", "achieve" and "life" used by the Russian president.</div></td></tr>
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</table>Olliehttps://sustainabilitymethods.org/index.php?title=Wordcloud&diff=5977&oldid=prevOllie: /* R Code */2021-07-05T16:29:03Z<p><span dir="auto"><span class="autocomment">R Code</span></span></p>
<table class="diff diff-contentalign-left" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 16:29, 5 July 2021</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l99" >Line 99:</td>
<td colspan="2" class="diff-lineno">Line 99:</td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div></syntaxhighlight></div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div></syntaxhighlight></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>[[File:PutinSpeech.png|500px|thumb|left|Fig.<del class="diffchange diffchange-inline">1</del>: Wordcloud of the most used words during Vladimir Putin's inauguration speech in 2016]]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>[[File:PutinSpeech.png|500px|thumb|left|Fig.<ins class="diffchange diffchange-inline">2</ins>: Wordcloud of the most used words during Vladimir Putin's inauguration speech in 2016]]</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>[[File:BidenSpeech.png|500px|thumb|center|Fig.<del class="diffchange diffchange-inline">1</del>: Wordcloud of the most used words during Joe Biden's inauguration speech in 2021]]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>[[File:BidenSpeech.png|500px|thumb|center|Fig.<ins class="diffchange diffchange-inline">3</ins>: Wordcloud of the most used words during Joe Biden's inauguration speech in 2021]]</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline"><br></del></div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline"><br></del></div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline">Above we see two wordclouds resulting from out text mining performed on the transcripts of Biden and Putin during their inauguration ceremonies. Based on the visualisations, we can conclude, that the most used word for both presidents were the names of their countries. Both presidents addressed the people by using different words, such as "people" and "citizens" in case of Vladimir Putin's speech, and "nation" and "Americans" in case of Biden's speech. Among other more prominent terms are such words as "democracy", "story", "war", "justice", "unity" and "work" used by the American president, and "challenges", "time", "history", "work", "towards", "fatherland", "achieve" and "life" used by the Russian president.</ins></div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline"><br></del></div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline"><br></del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==References and further reading material==</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==References and further reading material==</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The code was inspired by</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The code was inspired by</div></td></tr>
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</table>Olliehttps://sustainabilitymethods.org/index.php?title=Wordcloud&diff=5976&oldid=prevOllie: /* References and further reading material */2021-07-05T16:13:29Z<p><span dir="auto"><span class="autocomment">References and further reading material</span></span></p>
<table class="diff diff-contentalign-left" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 16:13, 5 July 2021</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l106" >Line 106:</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div><br></div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div><br></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==References and further reading material==</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==References and further reading material==</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>The code was <del class="diffchange diffchange-inline">inspied </del>by</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>The code was <ins class="diffchange diffchange-inline">inspired </ins>by</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># [https://anamumaq.medium.com/easy-word-cloud-with-r-perus-presidential-debate-version-a1911aa0f1e Easy word cloud with R — Peru’s presidential debate version] by Ana Muñoz Maquera</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># [https://anamumaq.medium.com/easy-word-cloud-with-r-perus-presidential-debate-version-a1911aa0f1e Easy word cloud with R — Peru’s presidential debate version] by Ana Muñoz Maquera</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># [https://medium.com/swlh/my-first-data-science-project-a-word-cloud-comparing-the-2020-presidential-debates-c4a2c705dae2 "My First Data Science Project: A Word Cloud Comparing the 2020 Presidential Debates"] by Tori White</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># [https://medium.com/swlh/my-first-data-science-project-a-word-cloud-comparing-the-2020-presidential-debates-c4a2c705dae2 "My First Data Science Project: A Word Cloud Comparing the 2020 Presidential Debates"] by Tori White</div></td></tr>
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</table>Olliehttps://sustainabilitymethods.org/index.php?title=Wordcloud&diff=5975&oldid=prevOllie at 16:12, 5 July 20212021-07-05T16:12:57Z<p></p>
<table class="diff diff-contentalign-left" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 16:12, 5 July 2021</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l101" >Line 101:</td>
<td colspan="2" class="diff-lineno">Line 101:</td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[File:PutinSpeech.png|500px|thumb|left|Fig.1: Wordcloud of the most used words during Vladimir Putin's inauguration speech in 2016]]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[File:PutinSpeech.png|500px|thumb|left|Fig.1: Wordcloud of the most used words during Vladimir Putin's inauguration speech in 2016]]</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[File:BidenSpeech.png|500px|thumb|center|Fig.1: Wordcloud of the most used words during Joe Biden's inauguration speech in 2021]]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[File:BidenSpeech.png|500px|thumb|center|Fig.1: Wordcloud of the most used words during Joe Biden's inauguration speech in 2021]]</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div> </div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline"><br></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline"><br></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline"><br></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline"><br></ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==References and further reading material==</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==References and further reading material==</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The code was inspied by</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The code was inspied by</div></td></tr>
<tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l107" >Line 107:</td>
<td colspan="2" class="diff-lineno">Line 110:</td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># [https://medium.com/swlh/my-first-data-science-project-a-word-cloud-comparing-the-2020-presidential-debates-c4a2c705dae2 "My First Data Science Project: A Word Cloud Comparing the 2020 Presidential Debates"] by Tori White</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># [https://medium.com/swlh/my-first-data-science-project-a-word-cloud-comparing-the-2020-presidential-debates-c4a2c705dae2 "My First Data Science Project: A Word Cloud Comparing the 2020 Presidential Debates"] by Tori White</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"><br></del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"><br></del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Further sources</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Further sources</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># [http://en.kremlin.ru/events/president/news/57416 The official transcript of the inaugural speech of the President of Russian (2016)] </div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># [http://en.kremlin.ru/events/president/news/57416 The official transcript of the inaugural speech of the President of Russian (2016)] </div></td></tr>
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</table>Olliehttps://sustainabilitymethods.org/index.php?title=Wordcloud&diff=5974&oldid=prevOllie at 16:12, 5 July 20212021-07-05T16:12:27Z<p></p>
<table class="diff diff-contentalign-left" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 16:12, 5 July 2021</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l107" >Line 107:</td>
<td colspan="2" class="diff-lineno">Line 107:</td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># [https://medium.com/swlh/my-first-data-science-project-a-word-cloud-comparing-the-2020-presidential-debates-c4a2c705dae2 "My First Data Science Project: A Word Cloud Comparing the 2020 Presidential Debates"] by Tori White</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># [https://medium.com/swlh/my-first-data-science-project-a-word-cloud-comparing-the-2020-presidential-debates-c4a2c705dae2 "My First Data Science Project: A Word Cloud Comparing the 2020 Presidential Debates"] by Tori White</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><br></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><br></ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Further sources</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Further sources</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># [http://en.kremlin.ru/events/president/news/57416 The official transcript of the inaugural speech of the President of Russian (2016)] </div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># [http://en.kremlin.ru/events/president/news/57416 The official transcript of the inaugural speech of the President of Russian (2016)] </div></td></tr>
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</table>Olliehttps://sustainabilitymethods.org/index.php?title=Wordcloud&diff=5973&oldid=prevOllie: /* R Code */2021-07-05T16:11:45Z<p><span dir="auto"><span class="autocomment">R Code</span></span></p>
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 16:11, 5 July 2021</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div></syntaxhighlight></div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div></syntaxhighlight></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>[[File:<del class="diffchange diffchange-inline">BidenSpeech</del>.png|<del class="diffchange diffchange-inline">350px</del>|thumb|<del class="diffchange diffchange-inline">center</del>|Fig.1: Wordcloud of the most used words during <del class="diffchange diffchange-inline">Joe Biden</del>'s inauguration speech in <del class="diffchange diffchange-inline">2021</del>]]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>[[File:<ins class="diffchange diffchange-inline">PutinSpeech</ins>.png|<ins class="diffchange diffchange-inline">500px</ins>|thumb|<ins class="diffchange diffchange-inline">left</ins>|Fig.1: Wordcloud of the most used words during <ins class="diffchange diffchange-inline">Vladimir Putin</ins>'s inauguration speech in <ins class="diffchange diffchange-inline">2016</ins>]]</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>[[File:<del class="diffchange diffchange-inline">PutinSpeech</del>.png|<del class="diffchange diffchange-inline">350px</del>|thumb|<del class="diffchange diffchange-inline">left</del>|Fig.1: Wordcloud of the most used words during <del class="diffchange diffchange-inline">Vladimir Putin</del>'s inauguration speech in <del class="diffchange diffchange-inline">2016</del>]]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>[[File:<ins class="diffchange diffchange-inline">BidenSpeech</ins>.png|<ins class="diffchange diffchange-inline">500px</ins>|thumb|<ins class="diffchange diffchange-inline">center</ins>|Fig.1: Wordcloud of the most used words during <ins class="diffchange diffchange-inline">Joe Biden</ins>'s inauguration speech in <ins class="diffchange diffchange-inline">2021</ins>]]</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==References and further reading material==</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==References and further reading material==</div></td></tr>
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