International Journal of Advance Computational Engineering and Networking (IJACEN)
.
Follow Us On :
current issues
Volume-12,Issue-1  ( Jan, 2024 )
Past issues
  1. Volume-11,Issue-12  ( Dec, 2023 )
  2. Volume-11,Issue-11  ( Nov, 2023 )
  3. Volume-11,Issue-10  ( Oct, 2023 )
  4. Volume-11,Issue-9  ( Sep, 2023 )
  5. Volume-11,Issue-8  ( Aug, 2023 )
  6. Volume-11,Issue-7  ( Jul, 2023 )
  7. Volume-11,Issue-6  ( Jun, 2023 )
  8. Volume-11,Issue-5  ( May, 2023 )
  9. Volume-11,Issue-4  ( Apr, 2023 )
  10. Volume-11,Issue-3  ( Mar, 2023 )

Statistics report
Apr. 2024
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 133
Paper Published : 1552
No. of Authors : 4025
  Journal Paper


Paper Title :
Rare Topic Discovery and User Behavior Analysis on Document Streams in Social Media

Author :Minu T Lalson, Kishore Sebastian

Article Citation :Minu T Lalson ,Kishore Sebastian , (2017 ) " Rare Topic Discovery and User Behavior Analysis on Document Streams in Social Media " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 37-40, Volume-5,Issue-7

Abstract : Internet contains document streams that are published in various forms like posts in social media, news streams, chats etc. Among these, documents published in social media get more focus. People use social media to express their opinion about various events. These document streams are based on some topic. Many people can talk on same topic. Therefore sequential topics can be obtained from these documents. These topics are related to some rare social events, which can happen on a particular location. Also these topics can characterize user behavior. The proposed system is a text mining approach which analyses text data from social media and discover topics related to rare events. It then analyses user’s behavior towards the topic. The system contains four modules: data collection, data preprocessing, rare topic discovery and user behavior analysis. The experiment is done on twitter data which show that this approach is useful in twitter like social media sites itself. Keywords - Document Streams, Rare Events, Social Media, Topic Discovery, User Behavior.

Type : Research paper

Published : Volume-5,Issue-7


DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-8544   View Here

Copyright: © Institute of Research and Journals

| PDF |
Viewed - 64
| Published on 2017-09-08
   
   
IRAJ Other Journals
IJACEN updates
Paper Submission is open now for upcoming Issue.
The Conference World

JOURNAL SUPPORTED BY