![]() ![]() Until now, the stancetaking framework has been applied only through qualitative analysis of small corpora. For example, epistemic stance indicates the speaker’s certainty about what is being expressed, and affective stance indicates the emotional position of the speaker with respect to the content (Ochs 1993). Various configurations of these three stance dimensions can account for a range of phenomena. The notion of stancetaking, based on the stance triangle approach of Du Bois ( 2007), captures the speaker’s (or writer)’s relationship to (a) the topic of discussion, (b) the interlocutor or audience, and (c) the talk (or writing) itself. Interpersonal stancetaking represents an attempt to unify many of these threads into a single theoretical framework (Jaffe 2009 Kiesling 2009). Our focus on stancetaking is related to a line of research on the annotation of interpersonal and extra-propositional aspects of language, which encompass topics such as affect, certainty, formality, politeness, and subjectivity. These quantitative analyses are supplemented by extensive qualitative analysis, highlighting the compatibility of computational and qualitative methods in synthesizing evidence about the creation of interactional meaning. We identify lexical features that characterize the extremes along each stancetaking dimension, and show that these stancetaking properties can be predicted with moderate accuracy from bag-of-words features, even with a relatively small labeled training set. Using these annotations, we investigate thread structure and linguistic properties of stancetaking in online conversations. We begin with annotations of three linked stance dimensions-affect, investment, and alignment-on 68 conversation threads from the online platform Reddit. In this article, we propose a new computational operationalization of interpersonal stancetaking. Theories of interactional stancetaking have been put forward as holistic accounts, but until now, these theories have been applied only through detailed qualitative analysis of (portions of) a few individual conversations. Computational researchers have succeeded in operationalizing sentiment, formality, and politeness, but each of these constructs captures only some aspects of social and relational meaning. ![]() In turn, language is used to reshape these relationships over the course of an interaction. Language is shaped by the relationships between the speaker/writer and the audience, the object of discussion, and the talk itself.
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