Detecting Cross-Cultural Differences Using a Multilingual Topic Model

Detecting Cross-Cultural Differences Using a Multilingual Topic Model E.D. Guti´errez1 Ekaterina Shutova2 Patricia Lichtenstein3 Gerard de Melo4 Luca Gilardi5 1 University of California, San Diego 2 Computer Laboratory, University of Cambridge 3 University of California, Merced 4 IIIS, Tsinghua University, 5 ICSI, Berkeley edg@icsi.berkeley.edu es407@cam.ac.uk tricia1@uchicago.edu gdm@demelo.org lucag@icsi.berkeley.edu Abstract Understanding cross-cultural differences has important implications for world affairs and many aspects of the life of society. Yet, the majority of text-mining methods to date focus on the analysis of monolingual texts. In con- trast, we present a statistical model that simul- taneously learns a set of common topics from multilingual, non-parallel data and automati- cally discovers the differences in perspectives on these topics across linguistic communities. We perform a behavioural evaluation of a sub- set of the differences identified by our model in English and Spanish to investigate their psy- chological validity. 1 Introduction Recent years have seen a growing interest in text- mining applications aimed at uncovering public opinions and social trends (Fader et al., 2007; Mon- roe et al., 2008; Gerrish and Blei, 2011; Pennac- chiotti and Popescu, 2011). They rest on the as- sumption that the language we use is indicative of our underlying worldviews. Research in cognitive and sociolinguistics suggests that linguistic varia- tion across communities systematically reflects dif- ferences in their cultural and moral models and goes beyond lexicon and grammar (K¨ovecses, 2004; Lakoff and Wehling, 2012). Cross-cultural differ- ences manifest themselves in text in a multitude of ways, most prominently through the use of explicit opinion vocabulary with respect to a certain topic (e.g. “policies that benefit the poor”), idiomatic and metaphorical language (e.g. “the company is spin- ning its wheels”) and other types of figurative lan- guage, such as irony or sarcasm. The connection between language, culture and reasoning remains one of the central research ques- tions in psychology. Thibodeau and Borodit- sky (2011) investigated how metaphors affect our decision-making. They presented two groups of hu- man subjects with two different texts about crime. In the first text, crime was metaphorically portrayed as a virus and in the second as a beast. The two groups were then asked a set of questions on how to tackle crime in the city. As a result, while the first group tended to opt for preventive measures (e.g. stronger social policies), the second group converged on punishment- or restraint-oriented mea- sures. According to Thibodeau and Boroditsky, their results demonstrate that metaphors have profound influence on how we conceptualize and act with re- spect to societal issues. This suggests that in order to gain a full understanding of social trends across pop- ulations, one needs to identify subtle but systematic linguistic differences that stem from the groups’ cul- tural backgrounds, expressed both literally and fig- uratively. Performing such an analysis by hand is labor-intensive and often impractical, particularly in a multilingual setting where expertise in all of the languages of interest may be rare. With the rise of blogging and social media, NLP techniques have been successfully used …

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