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Research Collection School Of Computing and Information Systems

2014

Machine learning

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Full-Text Articles in Engineering

Effects Of Training Datasets On Both The Extreme Learning Machine And Support Vector Machine For Target Audience Identification On Twitter, Siaw Ling Lo, David Cornforth, Raymond Chiong Dec 2014

Effects Of Training Datasets On Both The Extreme Learning Machine And Support Vector Machine For Target Audience Identification On Twitter, Siaw Ling Lo, David Cornforth, Raymond Chiong

Research Collection School Of Computing and Information Systems

The ability to identify or predict a target audience from the increasingly crowded social space will provide a company some competitive advantage over other companies. In this paper, we analyze various training datasets, which include Twitter contents of an account owner and its list of followers, using features generated in different ways for two machine learning approaches - the Extreme Learning Machine (ELM) and Support Vector Machine (SVM). Various configurations of the ELM and SVM have been evaluated. The results indicate that training datasets using features generated from the owner tweets achieve the best performance, relative to other feature sets. …


Identifying The High-Value Social Audience From Twitter Through Text-Mining Methods, Siaw Ling Lo, David Cornforth, Raymond Chiong Nov 2014

Identifying The High-Value Social Audience From Twitter Through Text-Mining Methods, Siaw Ling Lo, David Cornforth, Raymond Chiong

Research Collection School Of Computing and Information Systems

Doing business on social media has become a common practice for many companies these days. While the contents shared on Twitter and Facebook offer plenty of opportunities to uncover business insights, it remains a challenge to sift through the huge amount of social media data and identify the potential social audience who is highly likely to be interested in a particular company. In this paper, we analyze the Twitter content of an account owner and its list of followers through various text mining methods, which include fuzzy keyword matching, statistical topic modeling and machine learning approaches. We use tweets of …