Laurie Feldman

Also published as: Laurie Beth Feldman


2022

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Semantic Congruency Facilitates Memory for Emojis
Andriana L. Christofalos | Laurie Beth Feldman | Heather Sheridan
Proceedings of the Fifth International Workshop on Emoji Understanding and Applications in Social Media

Emojis can assume different relations with the sentence context in which they occur. While affective elaboration and emoji-word redundancy are frequently investigated in laboratory experiments, the role of emojis in inferential processes has received much less attention. Here, we used an online ratings task and a recognition memory task to investigate whether differences in emoji function within a sentence affect judgments of emoji-text coherence and subsequent recognition accuracy. Emojis that function as synonyms of a target word from the passages were rated as better fitting with the passage (more coherent) than emojis consistent with an inference from the passage, and both types of emojis were rated as more coherent than incongruent (unrelated) emojis. In a recognition test, emojis consistent with the semantic content of passages (synonym and inference emojis) were better recognized than incongruent emojis. Findings of the present study provide corroborating evidence that readers extract semantic information from emojis and then integrate it with surrounding passage content.

2016

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ANEW+: Automatic Expansion and Validation of Affective Norms of Words Lexicons in Multiple Languages
Samira Shaikh | Kit Cho | Tomek Strzalkowski | Laurie Feldman | John Lien | Ting Liu | George Aaron Broadwell
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

In this article we describe our method of automatically expanding an existing lexicon of words with affective valence scores. The automatic expansion process was done in English. In addition, we describe our procedure for automatically creating lexicons in languages where such resources may not previously exist. The foreign languages we discuss in this paper are Spanish, Russian and Farsi. We also describe the procedures to systematically validate our newly created resources. The main contributions of this work are: 1) A general method for expansion and creation of lexicons with scores of words on psychological constructs such as valence, arousal or dominance; and 2) a procedure for ensuring validity of the newly constructed resources.

2015

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Understanding Cultural Conflicts using Metaphors and Sociolinguistic Measures of Influence
Samira Shaikh | Tomek Strzalkowski | Sarah Taylor | John Lien | Ting Liu | George Aaron Broadwell | Laurie Feldman | Boris Yamrom | Kit Cho | Yuliya Peshkova
Proceedings of the Third Workshop on Metaphor in NLP

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.

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Computing Affect in Metaphors
Tomek Strzalkowski | Samira Shaikh | Kit Cho | George Aaron Broadwell | Laurie Feldman | Sarah Taylor | Boris Yamrom | Ting Liu | Ignacio Cases | Yuliya Peshkova | Kyle Elliot
Proceedings of the Second Workshop on Metaphor in NLP

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Discovering Conceptual Metaphors using Source Domain Spaces
Samira Shaikh | Tomek Strzalkowski | Kit Cho | Ting Liu | George Aaron Broadwell | Laurie Feldman | Sarah Taylor | Boris Yamrom | Ching-Sheng Lin | Ning Sa | Ignacio Cases | Yuliya Peshkova | Kyle Elliot
Proceedings of the 4th Workshop on Cognitive Aspects of the Lexicon (CogALex)

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