Enthusiasm and support: alternative sentiment classification for social movements on social media. Mishra, S., Agarwal, S., Guo, J., Phelps, K., Picco, J., & Diesner, J. In Proceedings of the 2014 ACM conference on Web science - WebSci '14, pages 261-262, 6, 2014. ACM Press. ![Enthusiasm and support: alternative sentiment classification for social movements on social media [link]](https://bibbase.org/img/filetypes/link.svg "link")
Website abstract bibtex We present a novel sentiment classifier particularly designed for modeling and analyzing social movements; capturing levels of support (supportive versus non-supportive) and degrees of enthusiasm (enthusiastic versus passive). The resulting computational solution can help organizations involved with social causes to disseminate messages in a more informed and effective fashion; potentially leading to greater impact. Our findings suggest that enthusiastic and supportive tweets are more prevalent in tweets about social causes than other types of tweets on Twitter.
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abstract = {We present a novel sentiment classifier particularly designed for modeling and analyzing social movements; capturing levels of support (supportive versus non-supportive) and degrees of enthusiasm (enthusiastic versus passive). The resulting computational solution can help organizations involved with social causes to disseminate messages in a more informed and effective fashion; potentially leading to greater impact. Our findings suggest that enthusiastic and supportive tweets are more prevalent in tweets about social causes than other types of tweets on Twitter.},
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author = {Mishra, Shubhanshu and Agarwal, Sneha and Guo, Jinlong and Phelps, Kirstin and Picco, Johna and Diesner, Jana},
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