Term Document Frequency (TDF) Method for Extracting User Posts and Emerging Events in Social Networks
S.S.Manivannan1, M.Iyapparaja2, M.Prasanna3, T.Velmurugan4, J.Prabhu5
1S.S.Manivannan, Associate Professor, SITE School, Vellore Institute of Technology, Vellore, Tamilnadu, India.
2M.Iyapparaja, Associate Professor, SITE School, Vellore Institute of Technology, Vellore, Tamilnadu, India.
3M.Prasanna, Associate Professor, SITE School, Vellore Institute of Technology, Vellore, Tamilnadu, India.
4T.Velmurugan, Associate Professor, SITE School, Vellore Institute of Technology, Vellore, Tamilnadu, India.
5J.Prabhu, Associate Professor, SITE School, Vellore Institute of Technology, Vellore, Tamilnadu, India.
Manuscript received on November 19, 2019. | Revised Manuscript received on November 29 2019. | Manuscript published on 30 November, 2019. | PP: 10047-10050 | Volume-8 Issue-4, November 2019. | Retrieval Number: D9496118419/2019©BEIESP | DOI: 10.35940/ijrte.D9496.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Social network is a place where people exchange and share data related to the current trends and events all over the world. This specific behavior of users made us concentrate on the logic that processing these data may lead us to the extracting the current topic of curiosity between the users. Applying data clustering technique like Term-document-Frequency (TDF) based approach over these data may leads us up to the mark but there will be little chance of negatives. We are going to do a likely medium that can give both usual mentioning behaviour of a consumer and also the frequency of users occurring in their mentions. It also works well even the data of the messages are very small information. These extracted emerging topic are shown to the user those who subscribe for the details.
Keywords: Mentions, Mentionee, Emerging Events, Social Network.
Scope of the Article: Social Networks.