TY - JOUR
T1 - Detecting trend and bursty keywords using characteristics of Twitter stream data
AU - Kim, Daehoon
AU - Kim, Daeyong
AU - Rho, Seungmin
AU - Hwang, Eenjun
PY - 2013
Y1 - 2013
N2 - Twitter is a very popular online social networking and micro-blogging service that enables its users to post and share text-based messages called tweets. The numbers of active users and tweets generated daily are enormous and hence they, collectively, can give crucial clues to several interesting problems such as public opinion analysis and hot trend detection. Especially, to find out hot issues and trends from tweets, detection of popular keywords is very important. In this paper, we propose a new scheme for detecting trend and bursty keywords from Twitter stream data. Our scheme is very robust in that it can handle typical usages such as various abbreviations, minor typing errors and spacing errors that occur very frequently when writing tweets on various mobile devices. We implemented a prototype system and performed various experiments to show the effectiveness of our scheme.
AB - Twitter is a very popular online social networking and micro-blogging service that enables its users to post and share text-based messages called tweets. The numbers of active users and tweets generated daily are enormous and hence they, collectively, can give crucial clues to several interesting problems such as public opinion analysis and hot trend detection. Especially, to find out hot issues and trends from tweets, detection of popular keywords is very important. In this paper, we propose a new scheme for detecting trend and bursty keywords from Twitter stream data. Our scheme is very robust in that it can handle typical usages such as various abbreviations, minor typing errors and spacing errors that occur very frequently when writing tweets on various mobile devices. We implemented a prototype system and performed various experiments to show the effectiveness of our scheme.
KW - Bursty keyword detection
KW - Keyword
KW - SNS
KW - Twitter
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M3 - Article
AN - SCOPUS:84876024066
SN - 1975-4094
VL - 7
SP - 209
EP - 220
JO - International Journal of Smart Home
JF - International Journal of Smart Home
IS - 1
ER -