Abstract
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).
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 8643 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | International Workshops on Data Mining and Decision Analytics for Public Health, Biologically Inspired Data Mining Techniques, Mobile Data Management, Mining, and Computing on Social Networks, Big Data Science and Engineering on E-Commerce, Cloud Service Discovery, MSMV-MBI, Scalable Dats Analytics, Data Mining and Decision Analytics for Public Health and Wellness, Algorithms for Large-Scale Information Processing in Knowledge Discovery, Data Mining in Social Networks, Data Mining in Biomedical informatics and Healthcare, Pattern Mining and Application of Big Data in conjunction with 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2014 |
|---|---|
| Country | Taiwan |
| City | Tainan |
| Period | 14-05-13 → 14-05-16 |
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All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
Cite this
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Competition component identification on twitter. / Yang, Cheng Huang; Chen, Ji De; Kao, Hung-Yu.
Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2014 International Workshops: DANTH, BDM, MobiSocial, BigEC, CloudSD, MSMV-MBI, SDA, DMDA-Health, ALSIP, SocNet, DMBIH, BigPMA, Revised Selected Papers. ed. / Wen-Chih Peng; Haixun Wang; Zhi-Hua Zhou; Tu Bao Ho; Vincent S. Tseng; Arbee L.P. Chen; James Bailey. Springer Verlag, 2014. p. 584-595 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8643).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Competition component identification on twitter
AU - Yang, Cheng Huang
AU - Chen, Ji De
AU - Kao, Hung-Yu
PY - 2014/1/1
Y1 - 2014/1/1
N2 - 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).
AB - 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).
UR - http://www.scopus.com/inward/record.url?scp=84915816844&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84915816844&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-13186-3_52
DO - 10.1007/978-3-319-13186-3_52
M3 - Conference contribution
AN - SCOPUS:84915816844
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 584
EP - 595
BT - Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2014 International Workshops
A2 - Peng, Wen-Chih
A2 - Wang, Haixun
A2 - Zhou, Zhi-Hua
A2 - Ho, Tu Bao
A2 - Tseng, Vincent S.
A2 - Chen, Arbee L.P.
A2 - Bailey, James
PB - Springer Verlag
ER -