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Words-of-wisdom search based on multi-dimensional sentiment vector

Published: 05 December 2011 Publication History

Abstract

With the rapid advance of the Internet, everybody has become able to obtain information from it easily. However. there are no systems which are available to extract and present information suitable to a user's sentiment. We propose a system that searches for information based on a user's sentiment. As described in this this paper, we propose a words-of-wisdom search system as a first step of the research. Specifically, we first propose a multi-dimensional sentiment vector based on Nakamura's proposed 10 categories of sentiments. Next, based on our experiment, we calculate the value of sentiment words included in words-of-wisdom. Subsequently we calculate the sentiment value of words-of-wisdom using a value of sentiment words. We developed a prototype system and conducted experiments.

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  • (2018)Semantic emotion-topic model in social media environmentJournal of Web Engineering10.5555/3370048.337005217:1-2(73-92)Online publication date: 1-Mar-2018
  • (2015)Followee recommendation based on topic extraction and sentiment analysis from tweetsProceedings of the 17th International Conference on Information Integration and Web-based Applications & Services10.1145/2837185.2837234(1-10)Online publication date: 11-Dec-2015
  • (2014)Role of Emoticons for Multidimensional Sentiment Analysis of TwitterProceedings of the 16th International Conference on Information Integration and Web-based Applications & Services10.1145/2684200.2684283(107-115)Online publication date: 4-Dec-2014

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  1. Words-of-wisdom search based on multi-dimensional sentiment vector

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    cover image ACM Other conferences
    iiWAS '11: Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services
    December 2011
    572 pages
    ISBN:9781450307840
    DOI:10.1145/2095536
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 05 December 2011

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    Author Tags

    1. multi-dimentional sentiment
    2. sentiment search
    3. words-of-wisdom

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    View all
    • (2018)Semantic emotion-topic model in social media environmentJournal of Web Engineering10.5555/3370048.337005217:1-2(73-92)Online publication date: 1-Mar-2018
    • (2015)Followee recommendation based on topic extraction and sentiment analysis from tweetsProceedings of the 17th International Conference on Information Integration and Web-based Applications & Services10.1145/2837185.2837234(1-10)Online publication date: 11-Dec-2015
    • (2014)Role of Emoticons for Multidimensional Sentiment Analysis of TwitterProceedings of the 16th International Conference on Information Integration and Web-based Applications & Services10.1145/2684200.2684283(107-115)Online publication date: 4-Dec-2014

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