This paper describes the development of an emoticon recommendation systembasedonusers’emotionalstatements.Inordertodevelopthissystem,aninnovative emoticon database consisting of a table of emoticons with points expressed fromeachof10distinctiveemotionswascreated.Anevaluationexperimentshowed that our proposed system achieved an improvement of 28.1 points over a baseline system, which recommends emoticons based on users’ past emoticon selection. We alsointegratedtheproposedandbaselinesystems,leadingtoaperformanceimprovement of approximately 73.0% in the same experiment. Evaluation of respondents’ perceptions of the three systems utilizing an SD scale and factor analysis is also described in this paper.
CITATION STYLE
Chen, C., Wu, K., Srinivasan, V., & Zhang, X. (2015). A Comprehensive Analysis of Detection of Online Paid Posters (pp. 101–118). https://doi.org/10.1007/978-3-319-14379-8_6
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