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Detecting Trending Topic on Chatter.
KTH, School of Computer Science and Communication (CSC).
2011 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The amount of posts on social network is overwhelming: for example Twitter has more than 50 millions posts a day. It has become crucial to be able to sort them. By detecting trending topics, which are topics the most discussed on a social network, we allow the user to instantly know what is happening in the network and if he is interesting in one topic, he can get access to all the posts related to this topic. In this work we present and compare different algorithms to detect trending topics. Our approach is to compute similarities between posts and then to find clusters in the graph of similarities using clustering algorithms.

Abstract [sv]

Chatter is designed to be the "Facebook for companies". One of the next challenges for Chatter is to implement the detection of trending topics. A trending topic is a topic discussed recently and a lot on a social network; this feature allows to know at a glance what is currently happening in the network and if he is interesting in one topic, he can get access to all the posts related to this topic. In this work we present and compare different algorithms to detect trending topics.The first approach is based on word-frequency, the second approach is to compute similarities between posts and then to find clusters in the graph of similarities using clustering algorithms. We also implement a service for collecting human inputs to evaluate the quality of the different algorithms.

Place, publisher, year, edition, pages
2011.
Series
Trita-CSC-E, ISSN 1653-5715 ; 2011:092
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-130676OAI: oai:DiVA.org:kth-130676DiVA: diva2:654123
Educational program
Master of Science in Engineering - Information and Communication Technology
Uppsok
Technology
Supervisors
Examiners
Available from: 2013-10-07 Created: 2013-10-07

Open Access in DiVA

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Other links

http://www.nada.kth.se/utbildning/grukth/exjobb/rapportlistor/2011/rapporter11/chaubet_jean-baptiste_11092.pdf
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School of Computer Science and Communication (CSC)
Computer Science

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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