Americans spend about a third of their time online, with many participating in online conversations on social and political issues. We hypothesize that social media arguments on such issues may be more engaging and persuasive than traditional media summaries, and that particular types of people may be more or less convinced by particular styles of argument, e.g. emotional arguments may resonate with some personalities while factual arguments resonate with others. We report a set of experiments testing at large scale how audience variables interact with argument style to affect the persuasiveness of an argument, an under-researched topic within natural language processing. We show that belief change is affected by personality factors, with conscientious, open and agreeable people being more convinced by emotional arguments.
@cite_67: The language used in online forums differs in many ways from that of traditional language resources such as news. One difference is the use and frequency of nonliteral, subjective dialogue acts such as sarcasm. Whether the aim is to develop a theory of sarcasm in dialogue, or engineer automatic methods for reliably detecting sarcasm, a major challenge is simply the difficulty of getting enough reliably labelled examples. In this paper we describe our work on methods for achieving highly reliable sarcasm annotations from untrained annotators on Mechanical Turk. We explore the use of a number of common statistical reliability measures, such as Kappa, Karger's, Majority Class, and EM. We show that more sophisticated measures do not appear to yield better results for our data than simple measures such as assuming that the correct label is the one that a majority of Turkers apply.
@cite_26: A study compared the communicative effectiveness of spontaneous monologues and dialogues on nonparticipating addressees overhearing talk. Overhearers were more accurate at following instructions in a referential communication task when listening in on dialogues than when listening in on monologues. Several extraneous variables could not account for the result. Two explanations for overhearers’ better performances on the dialogues are that the greater number of discourse markers helps overhearers follow the speech and that the perspectives of multiple interlocutors are more informative than one perspective. Extensions of the collaborative model of language use are discussed.
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@cite_55: 
@cite_42: It is important to investigate the influence of life-like agents interacting with a user since some studies suggest thai life-like agents can "persuade" people, in other words, they have potential to change people's attitude and behavior. In this study, the influence of overheard communication (OC), one of famous persuasion techniques, by life-like agents toward online shopping Web site users was examined, since the OC by people often changes attitude of receivers. An experiment to compare the effect of OC by two life-like agents (a persuader agent and a persuadee agent) with regular communication by one persuader agent were conducted. The result of this experiment implied that even the OC by life-like agents could promote Web site users' online shopping purchase likelihood. Moreover, despite impression to a life-like agent as a persuader was not strongly affected by OC, attractiveness toward a persuader agent evaluated by participants was positively correlated with their purchase likelihood. These results suggest the effectiveness of the OC by life-like agents and the new direction of studies of social response to life-like agents, from the viewpoints of presence, gaze, and appearance of lifelike agents.
@cite_1: We investigated the impact of dialogue and deep-level-reasoning questions on vicarious learning in 2 studies with undergraduates. In Experiment 1, participants learned material by interacting with AutoTutor or by viewing 1 of 4 vicarious learning conditions: a noninteractive recorded version of the AutoTutor dialogues, a dialogue with a deep-level-reasoning question preceding each sentence, a dialogue with a deep-level-reasoning question preceding half of the sentences, or a monologue. Learners in the condition where a deep-level-reasoning question preceded each sentence significantly outperformed those in the other 4 conditions. Experiment 2 included the same interactive and noninteractive recorded condition, along with 2 vicarious learning conditions involving deep-level-reasoning questions. Both deep-level-reasoning-question conditions significantly outperformed the other conditions. These findings provide evidence that deep-level-reasoning questions improve vicarious learning.
@cite_0: In two experiments, students overheard two computer-controlled virtual agents discussing four computer literacy topics in dialog discourse and four in monologue discourse. In Experiment 1, the virtual tutee asked a series of deep questions in the dialog condition, but only one per topic in the monologue condition in both studies. In the dialog conditions of Experiment 2, the virtual tutee asked either deep questions, shallow questions, or made comments. In a fourth “dialog” condition, the comments were spoken by the virtual tutor. The discourse spoken by the virtual tutor was identical in the dialog and monologue conditions, except in the fourth dialog condition. In both studies, learners wrote significantly more content and significantly more relevant content in the deep question condition than in the monologue condition. No other differences were significant. Results were discussed in terms of advanced organizers, schema theory, and discourse comprehension theory.
@cite_27: The role of dialogue in learning is considered with respect to the use of educational technology. The Vicarious Learner project aims to create a rehusable resource base of learning dialogues from which later learners can benefit. This depends on effective dialogues arising within computerhbased media, so that they can be captured. The conditions for effective dialogue are dependent not only on the technology, but on structures and conventions surrounding its use. Two studies are described, from which it emerges that new structures are needed. A notion of Task Directed Discussions (TDDs) is developed, through which effective dialogues are explicitly encouraged. A theoretical framework for the rehuse of such dialogues is described. © IFIP, published by Kluwer Academic Publishers
@cite_40: In 2 spontaneous speech experiments, this study found that multiple perspectives improved overhearers' abilities to select abstract shapes from an array, although single-perspective descriptions were more detailed. Prior findings that overhearers performed better when listening in on dialogues (Fox Tree, 1999) can best be understood as an advantage of the multiple-perspective descriptions that arise out of the entrainment process. Results support the collaborative theory of language use and suggest that vicarious learners would do better listening in on talk containing multiple perspectives than talk containing a single perspective.
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Previous work also tests the hypothesis that dialogic exchanges might be more engaging, in the context of expository or car sales dialog @cite_67 @cite_58 @cite_1 @cite_41 . Work comparing monologic vs. dialogic modes of providing information suggest that dialogs: (1) are more memorable and engaging, (2) stimulate the audience to formulate their own questions, and (3) allow audiences to be more successful at following communication @cite_27 @cite_26 @cite_42 @cite_0 @cite_40 @cite_26 @cite_55 .