Umit Boz


2014

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Automatic Expansion of the MRC Psycholinguistic Database Imageability Ratings
Ting Liu | Kit Cho | G. Aaron Broadwell | Samira Shaikh | Tomek Strzalkowski | John Lien | Sarah Taylor | Laurie Feldman | Boris Yamrom | Nick Webb | Umit Boz | Ignacio Cases | Ching-sheng Lin
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

Recent studies in metaphor extraction across several languages (Broadwell et al., 2013; Strzalkowski et al., 2013) have shown that word imageability ratings are highly correlated with the presence of metaphors in text. Information about imageability of words can be obtained from the MRC Psycholinguistic Database (MRCPD) for English words and Léxico Informatizado del Español Programa (LEXESP) for Spanish words, which is a collection of human ratings obtained in a series of controlled surveys. Unfortunately, word imageability ratings were collected for only a limited number of words: 9,240 words in English, 6,233 in Spanish; and are unavailable at all in the other two languages studied: Russian and Farsi. The present study describes an automated method for expanding the MRCPD by conferring imageability ratings over the synonyms and hyponyms of existing MRCPD words, as identified in Wordnet. The result is an expanded MRCPD+ database with imagea-bility scores for more than 100,000 words. The appropriateness of this expansion process is assessed by examining the structural coherence of the expanded set and by validating the expanded lexicon against human judgment. Finally, the performance of the metaphor extraction system is shown to improve significantly with the expanded database. This paper describes the process for English MRCPD+ and the resulting lexical resource. The process is analogous for other languages.

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A Multi-Cultural Repository of Automatically Discovered Linguistic and Conceptual Metaphors
Samira Shaikh | Tomek Strzalkowski | Ting Liu | George Aaron Broadwell | Boris Yamrom | Sarah Taylor | Laurie Feldman | Kit Cho | Umit Boz | Ignacio Cases | Yuliya Peshkova | Ching-Sheng Lin
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

In this article, we present details about our ongoing work towards building a repository of Linguistic and Conceptual Metaphors. This resource is being developed as part of our research effort into the large-scale detection of metaphors from unrestricted text. We have stored a large amount of automatically extracted metaphors in American English, Mexican Spanish, Russian and Iranian Farsi in a relational database, along with pertinent metadata associated with these metaphors. A substantial subset of the contents of our repository has been systematically validated via rigorous social science experiments. Using information stored in the repository, we are able to posit certain claims in a cross-cultural context about how peoples in these cultures (America, Mexico, Russia and Iran) view particular concepts related to Governance and Economic Inequality through the use of metaphor. Researchers in the field can use this resource as a reference of typical metaphors used across these cultures. In addition, it can be used to recognize metaphors of the same form or pattern, in other domains of research.

2013

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Robust Extraction of Metaphor from Novel Data
Tomek Strzalkowski | George Aaron Broadwell | Sarah Taylor | Laurie Feldman | Samira Shaikh | Ting Liu | Boris Yamrom | Kit Cho | Umit Boz | Ignacio Cases | Kyle Elliot
Proceedings of the First Workshop on Metaphor in NLP

2012

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Modeling Leadership and Influence in Multi-party Online Discourse
Tomek Strzalkowski | Samira Shaikh | Ting Liu | George Aaron Broadwell | Jenny Stromer-Galley | Sarah Taylor | Umit Boz | Veena Ravishankar | Xiaoai Ren
Proceedings of COLING 2012

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Extending the MPC corpus to Chinese and Urdu - A Multiparty Multi-Lingual Chat Corpus for Modeling Social Phenomena in Language
Ting Liu | Samira Shaikh | Tomek Strzalkowski | Aaron Broadwell | Jennifer Stromer-Galley | Sarah Taylor | Umit Boz | Xiaoai Ren | Jingsi Wu
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

In this paper, we report our efforts in building a multi-lingual multi-party online chat corpus in order to develop a firm understanding in a set of social constructs such as agenda control, influence, and leadership as well as to computationally model such constructs in online interactions. These automated models will help capture the dialogue dynamics that are essential for developing, among others, realistic human-machine dialogue systems, including autonomous virtual chat agents. In this paper, we first introduce our experiment design and data collection method in Chinese and Urdu, and then report on the current stage of our data collection. We annotated the collected corpus on four levels: communication links, dialogue acts, local topics, and meso-topics. Results from the analyses of annotated data on different languages indicate some interesting phenomena, which are reported in this paper.