The Word Feel as an Indicator of Enacted Social Support in Personal Relationships

Doell, Kelly

doi:10.5539/ijps.v5n4p107

Cited by 1 publication

(1 citation statement)

References 67 publications

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“…This class of features attempts to characterize the linguistic style of user utterances, including lexical choices that might be indicative of selfdisclosure (Doell, 2013). These include-i) Length of the user utterance, ii) Presence of negation words, iii) Part-of-speech tags such as nouns and adjectives in the user utterance in order to represent users revealing emotion or discussing topics, iv) Presence of filler words in utterance, v) Number of named entities in the utterance, vi) Gazeteer features based on common responses to questions asked by our dialog system, indicative of conversational responses as well as strongly positive, negative or neutral responses 4 .…”

Section: Linguistic Style Featuresmentioning

confidence: 99%

An Empirical Study of Self-Disclosure in Spoken Dialogue Systems

Ravichander¹,

Black²

2018

Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue

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Self-disclosure is a key social strategy employed in conversation to build relations and increase conversational depth. It has been heavily studied in psychology and linguistic literature, particularly for its ability to induce self-disclosure from the recipient, a phenomena known as reciprocity. However, we know little about how self-disclosure manifests in conversation with automated dialog systems, especially as any self-disclosure on the part of a dialog system is patently disingenuous. In this work, we run a large-scale quantitative analysis on the effect of selfdisclosure by analyzing interactions between real-world users and a spoken dialog system in the context of social conversation. We find that indicators of reciprocity occur even in human-machine dialog, with far-reaching implications for chatbots in a variety of domains including education, negotiation and social dialog.

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Section: Linguistic Style Featuresmentioning

confidence: 99%