Visible to the public Tweet Sentiment Analytics with Context Sensitive Tone-Word Lexicon

TitleTweet Sentiment Analytics with Context Sensitive Tone-Word Lexicon
Publication TypeConference Paper
Year of Publication2014
AuthorsBabour, A., Khan, J.I.
Conference NameWeb Intelligence (WI) and Intelligent Agent Technologies (IAT), 2014 IEEE/WIC/ACM International Joint Conferences on
Date PublishedAug
KeywordsAccuracy, Cameras, Context, context sensitive tone lexicon learning mechanism, data mining, Dictionaries, learning (artificial intelligence), natural language processing, opinion polarity mining, Semantics, sentiment analysis, social networking (online), text analysis, tone word polarity, tweet sentiment analytics, twitter sentiment analytics, word processing
Abstract

In this paper we propose a twitter sentiment analytics that mines for opinion polarity about a given topic. Most of current semantic sentiment analytics depends on polarity lexicons. However, many key tone words are frequently bipolar. In this paper we demonstrate a technique which can accommodate the bipolarity of tone words by context sensitive tone lexicon learning mechanism where the context is modeled by the semantic neighborhood of the main target. Performance analysis shows that ability to contextualize the tone word polarity significantly improves the accuracy.

DOI10.1109/WI-IAT.2014.61
Citation Key6927570