Modeling reciprocity in social interactions with probabilistic latent space models

Reciprocity is a pervasive concept that plays an important role in governing people’s behavior, judgments, and thus their social interactions. In this paper we present an analysis of the concept of reciprocity as expressed in English and a way to model it. At a larger structural level the reciprocity model will induce representations and clusters of relations between interpersonal verbs. In particular, we introduce an algorithm that semi-automatically discovers patterns encoding reciprocity based on a set of simple yet effective pronoun templates. Using the most frequently occurring patterns we queried the web and extracted 13,443 reciprocal instances, which represent a broad-coverage resource. Unsupervised clustering procedures are performed to generate meaningful semantic clusters of reciprocal instances. We also present several extensions (along with observations) to these models that incorporate metaattributes like the verbs’ affective value, identify gender differences bet...

• Type: Journal
• Year: 2011
• Where: NLE
• Authors: Roxana Girju, Michael J. Paul
• Keywords: Discovery Procedure, Natural Language Processing, NLE 2011, Pattern Discovery, Procedure Yields