{"id":1168,"date":"2026-01-25T19:28:26","date_gmt":"2026-01-25T19:28:26","guid":{"rendered":"https:\/\/www.cs.ubbcluj.ro\/~meco\/the-twitter-lex-sentiment-analysis-system-2022\/"},"modified":"2026-02-01T12:08:37","modified_gmt":"2026-02-01T12:08:37","slug":"the-twitter-lex-sentiment-analysis-system-2022","status":"publish","type":"post","link":"https:\/\/www.cs.ubbcluj.ro\/~meco\/the-twitter-lex-sentiment-analysis-system-2022\/","title":{"rendered":"The Twitter-Lex Sentiment Analysis System (2022)"},"content":{"rendered":"<div class=\"entry-content\">\n<p>International Conference on Knowledge Discovery and Information Retrieval<\/p>\n<h2>Authors<\/h2>\n<p>Sergiu Limboi, L. Dio\u015fan<\/p>\n<h2>Abstract<\/h2>\n<p>Twitter Sentiment Analysis is demanding due to the freestyle way people express their opinions and feelings. Using only the preprocessed text from a dataset does not bring enough value to the process. Therefore, there is a need to de\ufb01ne and mine different and complex features to detect hidden information from a tweet. The proposed Twitter-Lex Sentiment Analysis system combines lexicon features with Twitter-speci\ufb01c ones to improve the classi\ufb01cation performance. Therefore, several features are considered for the Sentiment Analysis process: only textual input from a tweet, hash-tags, and some \ufb02avors that combine them with the feature de\ufb01ned based on the result produced by a lexicon. So, the Vader lexicon is used to determine the sentiment of a tweet. This output will be appended to the four perspectives we de\ufb01ned, considering the features offered by Twitter. The experimental results reveal that our system, which focuses on the role of features in a classi\ufb01cation process, outperforms the baseline approach (use of original tweets) and provides good value to new directions and improvements.<\/p>\n<h2>Citation<\/h2>\n<pre class=\"wp-block-preformatted\">@Inproceedings{Limboi2022TheTS,\n author = {Sergiu Limboi and L. Dio\u015fan},\n booktitle = {International Conference on Knowledge Discovery and Information Retrieval},\n title = {The Twitter-Lex Sentiment Analysis System},\n year = {2022}\n}<\/pre>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Twitter Sentiment Analysis is demanding due to the freestyle way people express their opinions and feelings. Using only the preprocessed text from a dataset does not bring enough value to the process. Therefore, there is a need to de\ufb01ne and mine different and complex features to detect hidden information from a tweet. The proposed Twitter-Lex Sentiment Analysis system combines lexicon features with Twitter-speci\ufb01c ones to improve the classi\ufb01cation performance. Therefore, several features are considered for the Sentiment Analysis process: only textual input from a tweet, hash-tags, and some \ufb02avors that combine them with the feature de\ufb01ned based on the result produced by a lexicon. So, the Vader lexicon is used to determine the sentiment of a tweet. This output will be appended to the four perspectives we de\ufb01ned, considering the features offered by Twitter. The experimental results reveal that our system, which focuses on the role of features in a classi\ufb01cation process, outperforms the baseline approach (use of original tweets) and provides good value to new directions and improvements.<\/p>\n","protected":false},"author":6,"featured_media":0,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":[],"categories":[4],"tags":[9,30,31,25],"_links":{"self":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts\/1168"}],"collection":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/comments?post=1168"}],"version-history":[{"count":1,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts\/1168\/revisions"}],"predecessor-version":[{"id":1508,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts\/1168\/revisions\/1508"}],"wp:attachment":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/media?parent=1168"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/categories?post=1168"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/tags?post=1168"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}