Sentiment Analysis in Twitter for Macedonian
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Abstract (arXiv)
We present work on sentiment analysis in Twitter for Macedonian. As this is pioneering work for this combination of language and genre, we created suitable resources for training and evaluating a system for sentiment analysis of Macedonian tweets. In particular, we developed a corpus of tweets annotated with tweet-level sentiment polarity (positive, negative, and neutral), as well as with phrase-level sentiment, which we made freely available for research purposes. We further bootstrapped several large-scale sentiment lexicons for Macedonian, motivated by previous work for English. The impact of several different pre-processing steps as well as of various features is shown in experiments that represent the first attempt to build a system for sentiment analysis in Twitter for the morphologically rich Macedonian language. Overall, our experimental results show an F1-score of 92.16, which is very strong and is on par with the best results for English, which were achieved in recent SemEval competitions.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 8 of its 47 references that are in the map. First posted on arXiv 27 Sep 2021.
Builds on
8 of 47 references.
References · 8
- 2013NRC-Canada: Building the State-of-the-Art in Sentiment Analysis of Tweetscited by 33
- 2019SemEval-2013 Task 2: Sentiment Analysis in Twittercited by 22
- 2019SemEval-2014 Task 9: Sentiment Analysis in Twittercited by 20
- 2019SemEval-2015 Task 10: Sentiment Analysis in Twittercited by 16
- 2019Global Thread-Level Inference for Comment Classification in Community Question Answeringcited by 5
- 2021Exposing Paid Opinion Manipulation Trollscited by 3
- 2019Language-Independent Sentiment Analysis Using Subjectivity and Positional Informationcited by 2
- 2014Opinion mining of text documents written in Macedonian languagecited by 1
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Citing papers per year: 2022: 1.
1 paper.