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Empathy is a social mechanism used to support and strengthen emotional connection with others, including in online communities. However, little is currently known about the nature of these online expressions, nor the particular factors that may lead to their improved detection. In this work, we study the role of a specific and complex subcategory of linguistic phenomena, figurative language, in online expressions of empathy. Our extensive experiments reveal that incorporating features regarding the use of metaphor, idiom, and hyperbole into empathy detection models improves their performance, resulting in impressive maximum F1 scores of 0.942 and 0.809 for identifying posts without and with empathy, respectively.
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Effects of Situational Factors on Metaphor Detection in an Online Discussion Forum
Accurate metaphor detection remains an open challenge. In this paper, we explore a new type of clue for disambiguating terms that may be used metaphorically or literally in an online medical support community. In particular, we investigate the influence of situational factors on propensity to employ the metaphorical sense of words when they can be used to illustrate the emotion behind the experience of the event. Specifically we consider the experience of stressful illness-related events in a poster’s recent history as situational factors. We evaluate the positive impact of automatically extracted cancer events on a metaphor detection task using data from an online cancer forum. We also provide a discussion of specific associations between events and metaphors, such as journey with diagnosis or warrior with chemotherapy.
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- Award ID(s):
- 1302522
- PAR ID:
- 10080462
- Date Published:
- Journal Name:
- Third Workshop on Metaphor in NLP
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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