Detecting Common Discussion Topics Across Culture From News Reader Comments

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, pages 676–685, Berlin, Germany, August 7-12, 2016. c⃝2016 Association for Computational Linguistics Detecting Common Discussion Topics Across Culture From News Reader Comments Bei Shi1, Wai Lam1, Lidong Bing2 and Yinqing Xu1 1Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong, Hong Kong 2Machine Learning Department Carnegie Mellon University, Pittsburgh, PA 15213 {bshi,wlam,yqxu}@se.cuhk.edu.hk lbing@cs.cmu.edu Abstract News reader comments found in many on-line news websites are typically massive in amount. We investigate the task of Cultural-common Topic Detection (CTD), which is aimed at discovering common discussion topics from news reader comments written in different languages. We propose a new probabilistic graphical model called MCTA which can cope with the language gap and capture the common semantics in different languages. We also develop a partially collapsed Gibbs sampler which effectively incorporates the term trans- lation relationship into the detection of cultural-common topics for model param- eter learning. Experimental results show improvements over the state-of-the-art model. 1 Introduction Nowadays the rapid development of information and communication technology enables more and more people around the world to engage in the movement of globalization. One effect of global- ization is to facilitate greater connections between people bringing cultures closer than before. This also contributes to the convergence of some ele- ments of different cultures (Melluish, 2014). For example, there is a growing tendency of people watching the same movie, listening to the same music, and reading the news about the same event. This kind of cultural homogenization brings the emergence of commonality of some aspects of dif- ferent cultures worldwide. It would be beneficial to identify such common aspects among cultures. For example, it can provide some insights for global market and international business (Cavus- gil et al., 2014). Many news websites from different regions in the world report significant events which are of in- terests to people from different continents. These websites also allow readers around the world to give their comments in their own languages. The volume of comments is often enormous espe- cially for popular events. In a news website, readers from a particular culture background tend to write comments in their own preferred lan- guages. For some important or global events, we observe that readers from different cultures, via different languages, express common discus- sion topics. For instance, on March 8 2014, Malaysia Airlines Flight MH370, carrying 227 passengers and 12 crew members, disappeared. Upon the happening of this event, many news ar- ticles around the world reported it and many read- ers from different continents commented on this event. Through analyzing the reader comments manually, we observe that both English-speaking and Chinese-speaking readers expressed in their corresponding languages their desire for praying for the MH370 flight. This is an example of a cultural-common discussion topic. Identifying such cultural-common topics automatically can fa- cilitate better understanding and organization of the common concerns or interests of readers with different language background. Such technology can be deployed for …

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