中大學術數位典藏-NCU Institutional Repository-提供博碩士論文、考古題、期刊論文、研究計畫等下載:Item 987654321/106428
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 94274/94274 (100%)
Visitors : 82911083      Online Users : 2214
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version


    Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/106428


    Title: Building a graded Chinese sentiment dictionary based on commonsense knowledge for sentiment analysis of song lyrics
    Authors: 蔡宗翰;Wu), 吳蕙欣(Hui-Hsin;Tsai), 蔡長蓉(Angela Charng-Rurng;Tsai), 蔡宗翰(Richard Tzong-Han;Hsu), 許永真(Jane Yung-Jen
    Contributors: 資訊電機學院資訊工程學系
    Keywords: Algorithms;Data mining;Dictionaries;Extrapolation;Mandarins;Polarity;Social networks;Tasks
    Date: 2013-07-01
    Issue Date: 2026-04-23 13:22:19 (UTC+8)
    Publisher: Institute of Information Science;社團法人中華民國計算語言學學會
    Abstract: 摘要: With the rise of social media, sentiment analysis has become a popular research field in recent years. Sentiment dictionaries are vital for this task; however, there are few available in Chinese. Translated English sentiment dictionaries are often inaccurate or lacking vocabulary. Moreover, many dictionaries provide only binary polarity values or no values at all. In this paper, we integrate several common sentiment dictionaries into a larger dictionary. We then describe an algorithm that can extrapolate sentiment values for the empty entries in this dictionary from the annotated ones using the relationships in Chinese ConceptNet. The resulting iSentiDictionary is a Chinese sentiment dictionary with 28,248 concepts annotated with sentiment values. To test our dictionary, we construct a dictionary-based song lyrics sentiment analysis system. We compare performance of iSentiDictionary with that of three translated sentiment dictionaries: ANEW, SenticNet and SentiWordNet. Experimental results show that using iSentiDictionary achieves the best results in terms of both Word Coverage and Absolute Sentiment Error. We believe this is because of iSentiDictionary's high word coverage for Mandarin pop songs.
    出版者: 社團法人中華民國計算語言學學會
    出版日期: 2013-07-01
    出處: Journal of Information Science and Engineering, 2013-07, Vol.29 (4), p.647-662
    資源來源: Chinese Electronic Periodical Services (CEPS)
    識別號: ISSN: 1016-2364
    識別號: DOI: 10.6688/JISE.2013.29.4.3
    Appears in Collections:[Department of Computer Science and information Engineering] journal & Dissertation

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML19View/Open


    All items in NCUIR are protected by copyright, with all rights reserved.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 隱私權政策聲明