Deposition Control_ Becoming the Authority & Controlling the Conversation

Meeting proceedings of a seminar by the same name, held November 16, 2022

Deposition control: becoming the authority and controlling the conversation

Meeting proceedings of a seminar by the same name, held May 1, 2020

Perceived versus actual attitude similarity as predictors of change in interpersonal attraction

The present investigation was intended to identify factors that affect the degree to which interpersonal attraction changes over the course of face-to-face interaction. Participants completed a modified version of Byrne\u27s (1971) attitude questionnaire, the Crowne-Marlowe Social Desirability Scale (1964), and Snyder\u27s Self-Monitoring Scale and were then paired into attitudinally similar, dissimilar, or neutral dyads. Both before and after interacting for 40-minutes, dyads were asked to rate their interpersonal attraction toward their partner. Attitude similarity better predicted post-conversation interpersonal attraction when controlling for pre-conversation attraction than when not controlling for pre-conversation attraction. Social desirability, self-monitoring, and the coordination of vocal activity rhythms were not related to interpersonal attraction

Controlling the Conversation: The Ethics of Social Platforms and Content Moderation

With social platforms’ prevailing dominance, there are numerous debates around who owns information, content, and the audience itself: the publisher, or the platform where the content is discovered—or not discovered, as the case may be. Platforms rely heavily on algorithms to decide what to surface to their users across the globe, and they also rely on algorithms to decide what content is taken down. Meanwhile, publishers are making similar decisions on a significantly smaller scale, and not necessarily algorithmically or quite as generically. But how are any of these decisions made? And what are the various factors taken into account to ensure that the decision-making is fair and ethical? On February 23, 2018, the Tow Center for Digital Journalism at Columbia University and the Annenberg Innovation Lab at USC Annenberg School for Communication and Journalism hosted a Policy Exchange Forum followed by a conference on the topic of “Controlling the Conversation: The Ethics of Social Platforms and Content.” The Policy Exchange Forum was a closed-group discussion that followed the Chatham House Rule. The discussion broadly focused on three topics: “Ethics of Moderation”, “Moderation Tools”, and “Technological Challenges.

Consequences of Connection: Loneliness, Reading, and Robots

Modern communication technologies are reshaping the ways humans connect with one another as well as how we converse with machines of our own making. Our question in this essay is whether digital communication is changing the nature of conversation and, if so, what the implications may be for us as people. Our analysis identifies three sets of parameters for approaching these issues: linguistic (structure of conversations, communication medium, modulating the conversation to suit the perceived needs of our interlocutor, controlling the conversation), social (inner- or other-directed behavior, front stage or back stage behavior, strong or weak social ties, loneliness), and cognitive (level of intellectual engagement). We use these parameters to explore some of the linguistic, social, and cognitive consequences of electronically-mediated communication, of social reading onscreen, and of conversing with social robots

MojiTalk: Generating Emotional Responses at Scale

Generating emotional language is a key step towards building empathetic natural language processing agents. However, a major challenge for this line of research is the lack of large-scale labeled training data, and previous studies are limited to only small sets of human annotated sentiment labels. Additionally, explicitly controlling the emotion and sentiment of generated text is also difficult. In this paper, we take a more radical approach: we exploit the idea of leveraging Twitter data that are naturally labeled with emojis. More specifically, we collect a large corpus of Twitter conversations that include emojis in the response, and assume the emojis convey the underlying emotions of the sentence. We then introduce a reinforced conditional variational encoder approach to train a deep generative model on these conversations, which allows us to use emojis to control the emotion of the generated text. Experimentally, we show in our quantitative and qualitative analyses that the proposed models can successfully generate high-quality abstractive conversation responses in accordance with designated emotions

Informal Conversations and Power Play: A Case Study of Kashmiri Speech Community

Conversation forms an important part of human social life. People spend most of their time interacting with one another. Through conversation people command, argue, complain, etc. In any conversation, a speaker might tend to dominate the other speaker(s) by controlling their interactional behaviour, also known as “conversational dominance”. Various studies have been conducted wherein different conversational strategies like interruptions, turn taking, amount of talk, topic control, etc. have been considered as a measure of conversational power and dominance (Lakoff, 1975; Zimmerman and West, 1975; Ferguson, 1977; Tannen, 1993). The present paper is aimed at studying conversational dominance in informal settings of Kashmiri speech community. It will study the amount and distribution of interactional features like interruptions, turn taking, amount of talk and topic control in same-gender as well as mixed-gender multiparty conversations. This paper will attempt to relate these tools of conversational dominance with the socio-psychological factors of the participants. It will use Conversation Analysis (CA) approach to linguistic research