Computational measures for language similarity across time in online communities

Huffaker, David A.; Jorgensen, Joseph G.; Iacobelli, Francisco; Tepper, Paul; Cassell, Justine

doi:10.3115/1564535.1564538

Cited by 20 publications

(22 citation statements)

References 25 publications

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“…The control group also exhibited divergence in linguistic style, similar to previous research on communication in online community forums (Huffaker, Jorgensen, Iacobelli, Tepper, & Cassell, 2006;Jones et al, 2014), suggesting divergent communication is perhaps quite prevalent. Within CAT, divergence is usually a result of the desire to "emphasise distinctiveness from one's interlocutor" (Soliz & Giles, 2014, p. 5).…”

Section: Linguistic Style Divergence and Social Powersupporting

confidence: 82%

Characterizing the Linguistic Chameleon: Personal and Social Correlates of Linguistic Style Accommodation

et al. 2016

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Linguistic style accommodation between conversationalists is associated with positive social outcomes. We examine social power and personality as factors driving the occurrence of linguistic style accommodation, and the social outcomes of accommodation. Social power was manipulated to create 144 face‐to‐face dyadic interactions between individuals of high versus low power and 64 neutral power interactions. Particular configurations of personality traits (high self‐monitoring, Machiavellianism and leadership, and low self‐consciousness, impression management and agreeableness), combined with a low‐power role, led to an increased likelihood of linguistic style accommodation. Further, greater accommodation by low‐power individuals positively influenced perceptions of subjective rapport and attractiveness. We propose individual differences interact with social context to influence the conditions under which nonconscious communication accommodation occurs.

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Section: Linguistic Style Divergence and Social Powersupporting

confidence: 82%

Characterizing the Linguistic Chameleon: Personal and Social Correlates of Linguistic Style Accommodation

et al. 2016

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“…SCC was first proposed by Kilgarriff (2001) to measure the similarity between text and further evaluated by Huffaker et al (2006). Huffaker et al (2006) implemented SCC as the following: given a document pair (prime, target), for each document, rank the n common words in prime and target by frequency. For each word, let d be the difference of ranks in two documents.…”

Section: Spearman's Correlation Coefficientmentioning

confidence: 99%

An Evaluation and Comparison of Linguistic Alignment Measures

Reitter

2015

Proceedings of the 6th Workshop on Cognitive Modeling and Computational Linguistics

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Linguistic alignment has emerged as an important property of conversational language and a driver of mutual understanding in dialogue. While various computational measures of linguistic alignment in corpus and experimental data have been devised, a systematic evaluation of them is missing. In this study, we first evaluate the sensitivity and distributional properties of three measures, indiscriminate local linguistic alignment (LLA), Spearman's correlation coefficient (SCC), and repetition decay (RepDecay). Then we apply them in a study of interactive alignment and individual differences to see how well they conform to the Interactive Alignment Model (IAM), and how well they can reveal the individual differences in alignment propensity. Our results suggest that LLA has the overall best performance.

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“…Furthermore, in Huffaker et al (2006);Scissors et al (2008);Backstrom et al (2013) also show that people adjust their linguistic style, such as linguistic features, in the online written chatroom and online community. Also, priming effects at syntactic level (Gries, 2005;Branigan et al, 2000) have been explored in several written dataset settings (Pickering and Ferreira, 2008).…”

Section: Related Workmentioning

confidence: 99%

Proceedings of the Fifth Workshop on Cognitive Modeling and Computational Linguistics

2014

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followed in the tradition of earlier CMCL meetings, providing a venue for research in mathematical and computational psycholinguistics. We solicited papers on a broad spectrum of topics which spanned the formal modeling of language representation, development, and processing, and were very pleased to receive 17 submissions this year. The program below includes 8 of these papers which were selected for final presentation at the workshop. We would like to thank all submitting authors for the quality and variety of the papers we received, and for helping to foster the growth of the field of computational psycholinguistics. We would also like to thank our program committee for providing expertise in the evaluation of submitted papers. Finally, our program this year includes invited talks by Dr. Naomi Feldman of the University of Maryland and Dr. Edward Gibson of the Massachusetts Institute of Technology. We extend our appreciation to these researchers for sharing their work with us. Eye-movements in reading exhibit frequency spillover effects: fixation durations on a word are affected by the frequency of the previous word. We explore the idea that this effect may be an emergent property of a computationally rational eyemovement strategy that is navigating a tradeoff between processing immediate perceptual input, and continued processing of past input based on memory. We present an adaptive eye-movement control model with a minimal capacity for such processing, based on a composition of thresholded sequential samplers that integrate information from noisy perception and noisy memory. The model is applied to the List Lexical Decision Task and shown to yield frequency spillover-a robust property of human eye-movements in this task, even with parafoveal masking. We show that spillover in the model emerges in approximately optimal control policies that sometimes process memory rather than perception. We compare this model with one that is able to give priority to perception over memory, and show that the perception-priority policies in such a model do not perform as well in a range of plausible noise settings. We explain how the frequency spillover arises from a counter-intuitive but fundamental property of sequenced thresholded samplers. Introduction and overviewOur interest is in understanding how eyemovements are controlled in service of linguistic tasks involving reading-more specifically, how saccadic decisions are conditioned on the moment-by-moment state of incremental perceptual and cognitive processing. The phenomena we are concerned with here are spillover effects, where fixation durations on a word are affected by linguistic properties of the prior word or words. The specific idea we explore is that spillover effects may be emergent properties of a computationally rational control strategy that is navigating a tradeoff between processing immediate perceptual input, and continued processing of past input based on a memory of recent stimuli. The paper is organized as follows. We first review evidence that eye-m...

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Computational measures for language similarity across time in online communities

Cited by 20 publications

References 25 publications

Characterizing the Linguistic Chameleon: Personal and Social Correlates of Linguistic Style Accommodation

Characterizing the Linguistic Chameleon: Personal and Social Correlates of Linguistic Style Accommodation

An Evaluation and Comparison of Linguistic Alignment Measures

Proceedings of the Fifth Workshop on Cognitive Modeling and Computational Linguistics

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