| Autor: |
Adwan, Omar Y., Al-Tawil, Marwan, Huneiti, Ammar M., Shahin, Rawan A., Zayed, Abeer A. Abu, Al-Dibsi, Razan H. |
| Předmět: |
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| Zdroj: |
International Journal of Emerging Technologies in Learning; 2020, Vol. 15 Issue 15, p79-93, 15p |
| Abstrakt: |
Twitter is one of the most popular microblogging and social networking platforms where massive instant messages (i.e. tweets) are posted every day. Twitter sentiment analysis tackles the problem of analyzing users' tweets in terms of thoughts, interests and opinions in a variety of contexts and domains. Such analysis can be valuable for several researchers and applications that require understanding people views about a particular topic or event. The study carried out in this paper provides an overview of the algorithms and approaches that have been used for sentiment analysis in twitter. The reviewed articles are categories into four categories based on the approach they use. Furthermore, we discuss directions for future research on how twitter sentiment analysis approaches can utilize theories and technologies from other fields such cognitive science, semantic Web, big data and visualization. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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