{"id":3775,"date":"2024-01-15T12:58:24","date_gmt":"2024-01-15T11:58:24","guid":{"rendered":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/attempt-of-monitoring-of-social-tension-from-posts-on-the-facebook-social-networking-website\/"},"modified":"2024-01-17T13:25:25","modified_gmt":"2024-01-17T12:25:25","slug":"attempt-of-monitoring-of-social-tension-from-posts-on-the-facebook-social-networking-website","status":"publish","type":"post","link":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/attempt-of-monitoring-of-social-tension-from-posts-on-the-facebook-social-networking-website\/?lang=en","title":{"rendered":"Attempt of monitoring of social tension from posts on the Facebook social networking website"},"content":{"rendered":"

Dagmar Ce\u013euchov\u00e1 Bo\u0161ansk\u00e1, Martin Jan\u00edk, Filip Nguyen, Alistiq, s. r. o., Slovak Republic<\/p>\n

<\/p>\n

Type of article: informative article
\nPages: 93 – 110<\/p>\n

Abstract<\/h5>\n

Social networks are an increasingly popular place where people share their feelings and opinions on various events and thematically related topics. This popularity creates a large amount of data regarding people’s mood and social tension. The aim as to analyze the sentiment of the posts on the social networking website Facebook in Slovak and to use this data to obtain information about the emotional state of people. This method uses the natural language processing model XLM-RoBERTa-large and allows social tensions to be correlated with real-world events. Sentiment analysis of social media posts can be useful for policymakers and sociologists, and may be extended to other platforms and languages in the future.<\/p>\n

\n

Issue for download<\/span>
\n<\/i> PDF<\/a> (2,6 MB, 333 downloads)<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Dagmar Ce\u013euchov\u00e1 Bo\u0161ansk\u00e1, Martin Jan\u00edk, Filip Nguyen, Alistiq, s. r. o., Slovak Republic<\/p>\n","protected":false},"author":8,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"categories":[1725],"tags":[1733,1735,1734,1739,1663,1736,1737,1738],"class_list":["post-3775","post","type-post","status-publish","format-standard","hentry","category-1-2024-informative-articles-opinions-reviews-interviews-information","tag-author-dagmar-celuchova-bosanska","tag-author-filip-nguyen","tag-author-martin-janik","tag-data-mining","tag-machine-learning","tag-sentiment-analysis","tag-social-networks","tag-social-tension"],"_links":{"self":[{"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/posts\/3775","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/comments?post=3775"}],"version-history":[{"count":5,"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/posts\/3775\/revisions"}],"predecessor-version":[{"id":3866,"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/posts\/3775\/revisions\/3866"}],"wp:attachment":[{"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/media?parent=3775"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/categories?post=3775"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/tags?post=3775"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}