Competition Component Identification on Twitter

被引:0
|
作者
Yang, Cheng-Huang [1 ]
Chen, Ji-De [1 ]
Kao, Hung-Yu [1 ]
机构
[1] Natl Cheng Kung Univ, Dept Comp Sci & Informat Engn, Tainan 70101, Taiwan
来源
TRENDS AND APPLICATIONS IN KNOWLEDGE DISCOVERY AND DATA MINING | 2014年 / 8643卷
关键词
Twitter; Microblog; Opinion mining; Sentiment analysis;
D O I
10.1007/978-3-319-13186-3_52
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Twitter becomes a popular microblogging platform that let people to express their opinions on the web in recent years. Companies with new products always want to find consumers or public opinions about their products and services after they released new products. Due to this reason, more and more researchers use the opinion mining technology on this microblog media that contains abundant and real-time information, to extract useful opinions and information. In this paper, we aim to mine the opinions on Twitter and further extract the competition relations discussed on Twitter. For Example, if we want to know how people express their opinion about "Packer" (an American football team name), we also want to know what the Packer's competitors are. In this paper, we introduce a hashtag graph and use the ranks in this graph to represent the competition behavior and competition components (competitors).
引用
收藏
页码:584 / 595
页数:12
相关论文
共 50 条
  • [21] Automatic Identification and Classification of Misogynistic Language on Twitter
    Anzovino, Maria
    Fersini, Elisabetta
    Rosso, Paolo
    NATURAL LANGUAGE PROCESSING AND INFORMATION SYSTEMS (NLDB 2018), 2018, 10859 : 57 - 64
  • [22] A Turkish Dataset for Gender Identification of Twitter Users
    Sezerer, Erhan
    Polatbilek, Ozan
    Tekir, Selma
    13TH LINGUISTIC ANNOTATION WORKSHOP (LAW XIII), 2019, : 203 - 207
  • [23] Topic Identification System to Filter Twitter Feeds
    Altammami, Shatha Hamad
    Rana, Omer F.
    2016 3RD INTERNATIONAL CONFERENCE ON SOFT COMPUTING & MACHINE INTELLIGENCE (ISCMI 2016), 2016, : 206 - 213
  • [24] A visual approach for age and gender identification on Twitter
    Alvarez-Carmona, Miguel A.
    Pellegrin, Luis
    Montes-y-Gomez, Manuel
    Sanchez-Vega, Fernando
    Jair Escalante, Hugo
    Lopez-Monroy, A. Pastor
    Villasenor-Pineda, Luis
    Villatoro-Tello, Esau
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2018, 34 (05) : 3133 - 3145
  • [25] Predictive modeling for suspicious content identification on Twitter
    Surendra Singh Gangwar
    Santosh Singh Rathore
    Satyendra Singh Chouhan
    Sanskar Soni
    Social Network Analysis and Mining, 2022, 12
  • [26] Hyperlocal Home Location Identification of Twitter Profiles
    Poulston, Adam
    Stevenson, Mark
    Bontcheva, Kalina
    PROCEEDINGS OF THE 28TH ACM CONFERENCE ON HYPERTEXT AND SOCIAL MEDIA (HT'17), 2017, : 45 - 54
  • [27] Sentiment identification on Twitter using machine learning
    Morales-Castro, Wendy
    Careta, Eduardo Perez
    Rayas, Angelica Hernandez
    Mukhopadhyay, Tirtha Prasad
    Crespo, J. Armando Perez
    Cabrera, Rafael Guzman
    2022 EURO-ASIA CONFERENCE ON FRONTIERS OF COMPUTER SCIENCE AND INFORMATION TECHNOLOGY, FCSIT, 2022, : 28 - 31
  • [28] Predictive modeling for suspicious content identification on Twitter
    Gangwar, Surendra Singh
    Rathore, Santosh Singh
    Chouhan, Satyendra Singh
    Soni, Sanskar
    SOCIAL NETWORK ANALYSIS AND MINING, 2022, 12 (01)
  • [29] Probabilistic Component Identification
    Sajnani, Hitesh S.
    Lopes, Cristina V.
    PROCEEDINGS OF THE 7TH INDIA SOFTWARE ENGINEERING CONFERENCE 2014, ISEC '14, 2014,
  • [30] FLAVOR COMPONENT IDENTIFICATION
    CHANG, SS
    FOOD TECHNOLOGY, 1973, 27 (04) : 27 - &