Detecting the Likely Causes behind the Emotion Spikes of Influential Twitter Users for Arabic language
Journal Title: International Journal of engineering Research and Applications - Year 2018, Vol 8, Issue 9
Abstract
To our knowledge all the previous researches and studies for extracting the likely cause of emotion spikes was for comments and reviews with non-Arabic languages. Although, According to a study performed by Semiocast , Arabic was the fastest growing language on Twitter in 2011, and was the 6th most used language on Twitter in 2012. While a wide range of Arabic opinionated posts are broadcasted, research in the area of Arabic sentiment analysis remain sparse and show a very slow progress compared to that being carried out in other languages, mainly in English . For that, our work will be to identifying the likely causes of strong and sudden change of emotions within the temporal dimension of influential users’ emotion flow in Arabic Twitter we chose twitter because Twitter as a microblogging platform, receives over 500 million tweets worldwide every day as per 2016.These emotion spikes are the reaction of users toward certain events. Hence, our system will try to extracts keyphrases, which associated with each identified emotion spike, and passes them to an analyze step. Then the system will detect the named-entities and events or topics identification since the extracted keyphrases indicate a change on user’s emotions, and represent the causes of a particular emotion spike.
Authors and Affiliations
Entesar Eljali, Can Vurdu, Tarik Ahmad
Keywords
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