DocumentCode :
1793643
Title :
Prediction of interest for dynamic profile of Twitter user
Author :
Siswanto, Elisafina ; Khodra, Masayu Leylia ; Dewi, Luh Joni Erawati
Author_Institution :
Sch. of Electr. Eng. & Inf., Inst. Teknol. Bandung Bandung, Bandung, Indonesia
fYear :
2014
fDate :
20-21 Aug. 2014
Firstpage :
266
Lastpage :
271
Abstract :
Numerous studies have been conducted to explore the social network of Twitter; some have been conducted to predict the interest or the topic of the user´s tweet. In this study, we investigate the best classification model for determining the user´s interest based on the bio and a collection of tweets. We use the supervised learning-based classification with the lexical features. Two approaches were proposed; they are the classification that was made based on the user´s tweet using multilabel classification method and the classification that was made based on specific accounts. From the result of experimental result, it could be concluded that the employment of the classification using specific accounts approach led to better accuracy.
Keywords :
learning (artificial intelligence); pattern classification; social networking (online); Twitter user dynamic profile; interest prediction; lexical features; multilabel classification method; social network; supervised learning-based classification; Accuracy; Entertainment industry; Informatics; Support vector machines; Testing; Training data; Twitter; Twitter; classification; interest; lexical; machiney training; topic;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Informatics: Concept, Theory and Application (ICAICTA), 2014 International Conference of
Conference_Location :
Bandung
Print_ISBN :
978-1-4799-6984-5
Type :
conf
DOI :
10.1109/ICAICTA.2014.7005952
Filename :
7005952
Link To Document :
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