PhD Dissertation Defense by Agus SULISTYA | Making Sense of Crowd-Generated Content in Domain-Specific Settings

About The Talk

The rapid advances of the Internet have changed the ways information is distributed and exchanged among individuals and organizations. Various contents from different domains are generated daily, contributed by users' daily activities, such as posting messages in a microblog platform, or collaborating in a question-and-answer site. Engaging actively with such tremendous volume of user generated contents has now become a daily challenge for both organizations and end users. Work presented as part of this dissertation proposal aims to help both organizations and individuals make sense of such data considering domain-specific settings and tasks.

This dissertation highlights three pieces of completed work. The first work helps companies adapt customer service strategies by predicting a customer’s feedback behavior from his/her first feedback tweet. The second work predicts readers’ emotion distribution affected by a news article. By employing this work, publishers (e.g., news portals) can get insights into expected public response to a particular article, before they actually publish it. For the final work of this dissertation, an approach was proposed to improve the effectiveness of knowledge extraction tasks by performing cross-platform analysis to help knowledge workers better make sense of domain-specific data.

Speaker Biography

Agus SULISTYA is a PhD candidate (since 2014) in School of Information Systems, Singapore Management University. He is supervised by Associate Professor David LO and Professor LIM Ee-Peng. His research interests are in application of data mining and text analysis in organization and social context. Agus holds a B.S in Computer Science from Telkom University, and M.S in Information Systems from Northeastern University. Before starting his PhD, Agus worked at PT Telekomunikasi Indonesia.