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Characterizing the effectiveness of twitter hashtags to detect and track online population sentiment

Published: 05 May 2012 Publication History

Abstract

In this paper we describe the preliminary results and future directions of a research in progress, which aims at assessing the hashtag effectiveness as a resource for sentiment analysis expressed on Twitter. The results so far support our hypothesis that hashtags may facilitate the detection and automatic tracking of online population sentiment about different events.

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    cover image ACM Conferences
    CHI EA '12: CHI '12 Extended Abstracts on Human Factors in Computing Systems
    May 2012
    2864 pages
    ISBN:9781450310161
    DOI:10.1145/2212776

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    New York, NY, United States

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    Published: 05 May 2012

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    Author Tags

    1. hashtag
    2. social phenomena
    3. twitter
    4. user sentiment analysis

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    • (2020)Anonymous Real-Time Analytics Monitoring Solution for Decision Making Supported by Sentiment AnalysisSensors10.3390/s2016455720:16(4557)Online publication date: 14-Aug-2020
    • (2019)Identifying and Analyzing Different Aspects of English-Hindi Code-Switching in TwitterACM Transactions on Asian and Low-Resource Language Information Processing10.1145/331493518:3(1-28)Online publication date: 23-Jul-2019
    • (2018)TagNet: Toward Tag-Based Sentiment Analysis of Large Social Media Data2018 IEEE Pacific Visualization Symposium (PacificVis)10.1109/PacificVis.2018.00032(190-194)Online publication date: Apr-2018
    • (2018)A Deep Learning Approach for Sentiment Analysis in Spanish TweetsArtificial Neural Networks and Machine Learning – ICANN 201810.1007/978-3-030-01424-7_61(622-629)Online publication date: 27-Sep-2018
    • (2017)Social media analysis during political turbulencePLOS ONE10.1371/journal.pone.018683612:10(e0186836)Online publication date: 31-Oct-2017
    • (2016)Investigating the complete corpus of referendum and elections tweetsProceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.5555/3192424.3192443(100-105)Online publication date: 18-Aug-2016
    • (2016)Can Visualization Techniques Help Journalists to Deepen Analysis of Twitter Data? Exploring the "Germany 7 x 1 Brazil" CaseProceedings of the 2016 49th Hawaii International Conference on System Sciences (HICSS)10.1109/HICSS.2016.245(1939-1948)Online publication date: 5-Jan-2016
    • (2016)Investigating the complete corpus of referendum and elections tweets2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)10.1109/ASONAM.2016.7752220(100-105)Online publication date: Aug-2016
    • (2015)Detecting sociosemantic communities by applying social network analysis in tweetsSocial Network Analysis and Mining10.1007/s13278-015-0280-25:1Online publication date: 9-Jul-2015
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