Biplot of most engaged topics for both news and parties datasets.
<p>Close points and vectors suggest similar profiles.</p>
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , |
| منشور في: |
2025
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| الموضوعات: | |
| الوسوم: |
إضافة وسم
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| _version_ | 1852023005245341696 |
|---|---|
| author | Giulio Pecile (20678050) |
| author2 | Niccolò Di Marco (14173530) Matteo Cinelli (8575176) Walter Quattrociocchi (522167) |
| author2_role | author author author |
| author_facet | Giulio Pecile (20678050) Niccolò Di Marco (14173530) Matteo Cinelli (8575176) Walter Quattrociocchi (522167) |
| author_role | author |
| dc.creator.none.fl_str_mv | Giulio Pecile (20678050) Niccolò Di Marco (14173530) Matteo Cinelli (8575176) Walter Quattrociocchi (522167) |
| dc.date.none.fl_str_mv | 2025-02-05T18:22:24Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0316271.g004 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Biplot_of_most_engaged_topics_for_both_news_and_parties_datasets_/28352857 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Cell Biology Neuroscience Biotechnology Evolutionary Biology Ecology Science Policy Biological Sciences not elsewhere classified major news outlets measuring public engagement identifying key topics global election landscape 2024 </ p user engagement media landscape global population xlink "> users behave uncover patterns study examines social media significant portion providing insights political parties political ideology political discourse media content information spreads findings show distinguish trends audience interaction analyzing posts |
| dc.title.none.fl_str_mv | Biplot of most engaged topics for both news and parties datasets. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>Close points and vectors suggest similar profiles.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_3eb75fcdd50bed73fbd602bbf29ead85 |
| identifier_str_mv | 10.1371/journal.pone.0316271.g004 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/28352857 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Biplot of most engaged topics for both news and parties datasets.Giulio Pecile (20678050)Niccolò Di Marco (14173530)Matteo Cinelli (8575176)Walter Quattrociocchi (522167)Cell BiologyNeuroscienceBiotechnologyEvolutionary BiologyEcologyScience PolicyBiological Sciences not elsewhere classifiedmajor news outletsmeasuring public engagementidentifying key topicsglobal election landscape2024 </ puser engagementmedia landscapeglobal populationxlink ">users behaveuncover patternsstudy examinessocial mediasignificant portionproviding insightspolitical partiespolitical ideologypolitical discoursemedia contentinformation spreadsfindings showdistinguish trendsaudience interactionanalyzing posts<p>Close points and vectors suggest similar profiles.</p>2025-02-05T18:22:24ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0316271.g004https://figshare.com/articles/figure/Biplot_of_most_engaged_topics_for_both_news_and_parties_datasets_/28352857CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/283528572025-02-05T18:22:24Z |
| spellingShingle | Biplot of most engaged topics for both news and parties datasets. Giulio Pecile (20678050) Cell Biology Neuroscience Biotechnology Evolutionary Biology Ecology Science Policy Biological Sciences not elsewhere classified major news outlets measuring public engagement identifying key topics global election landscape 2024 </ p user engagement media landscape global population xlink "> users behave uncover patterns study examines social media significant portion providing insights political parties political ideology political discourse media content information spreads findings show distinguish trends audience interaction analyzing posts |
| status_str | publishedVersion |
| title | Biplot of most engaged topics for both news and parties datasets. |
| title_full | Biplot of most engaged topics for both news and parties datasets. |
| title_fullStr | Biplot of most engaged topics for both news and parties datasets. |
| title_full_unstemmed | Biplot of most engaged topics for both news and parties datasets. |
| title_short | Biplot of most engaged topics for both news and parties datasets. |
| title_sort | Biplot of most engaged topics for both news and parties datasets. |
| topic | Cell Biology Neuroscience Biotechnology Evolutionary Biology Ecology Science Policy Biological Sciences not elsewhere classified major news outlets measuring public engagement identifying key topics global election landscape 2024 </ p user engagement media landscape global population xlink "> users behave uncover patterns study examines social media significant portion providing insights political parties political ideology political discourse media content information spreads findings show distinguish trends audience interaction analyzing posts |