9,280 research outputs found

    Innocent Until Proven Guilty: Suspicion of Deception in Online Reviews

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    - Purpose: This study formulates a new framework for identifying deception in consumer reviews through the lens of Interpersonal Deception Theory and the Persuasion Knowledge Model. It evaluates variables contributing to consumer intentions to purchase after reading deceptive reviews and proposes deception identification cues to be incorporated into the interpersonal communication theoretical framework. - Methodology: The first study is qualitative and quantitative, based on sentiment and lexical analysis of 1000 consumer reviews. The second study employs a USA national consumer survey with a PLS-SEM and a Process-based mediation-moderation analysis. - Findings: The study shows deceptive characteristics that cannot be dissimulated by reviewing consumers that represent review legitimacy based on review valence, authenticity, formalism, and analytical writing. The results also support the central role of consumer suspicion of an ulterior motive, with a direct and mediation effect regarding consumer emotions and intentions, including brand trust and purchase intentions. - Research implications: This paper presents a new framework for identifying deception in consumer reviews based on IDT and PKM, adding new theoretical elements that help adapt these theories to written digital communication specificities. The study clarifies the role of suspicion in a deceptive communication context and shows the variables contributing to consumers’ purchase intention after reading deceptive reviews. The results also emphasize the benefits of lexical analysis in identifying deceptive characteristics of reviews. - Practical implications: Companies can consider the vulnerability of certain generations based on lower levels of suspicions and different linguistic cues to detect deception in reviews. Long-term, marketers can also implement deception identification practices as potential new business models and opportunities. - Social implications: Policymakers and regulators need to consider critical deception cues and the differences in suspicion levels among segments of consumers in the formulation of preventative and deception management measures. - Originality/value: This study contributes to the literature by formulating a new framework for identifying deception in consumer reviews, adapted to the characteristics of written digital communication. The study emphasizes deception cues in eWOM and provides additional opportunities for theorizing deception in electronic communication

    The Linguistic Features of Deceptive Speech

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    Research on deception within the field of linguistics has been largely focused upon the lexical aspect of lies. However, while the words a liar uses may reveal the lie in some cases, there are certain prosodic features of speech (e.g. pitch or tempo) that may be correlated to lying. This study focuses on these features in an attempt to decode deception. In an experiment with a representative sample of a university campus population, participants were asked to lie for science in a game of ‘Two Truths and a Lie’. Each participant’s speech was recorded while they constructed spontaneous truths and lies. Participants were then asked to complete a post-experiment survey in an effort to gauge their perceptions on lying; this was done in an effort to determine if their perceptions may influence the lies they tell. The resulting data were subjected to acoustic analysis to quantify their prosodic features, which were subsequently analyzed statistically to determine the presence, and strength, of any correlation between these characteristics of speech and deception

    The civilizing process in London’s Old Bailey

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    The jury trial is a critical point where the state and its citizens come together to define the limits of acceptable behavior. Here we present a large-scale quantitative analysis of trial transcripts from the Old Bailey that reveal a major transition in the nature of this defining moment. By coarse-graining the spoken word testimony into synonym sets and dividing the trials based on indictment, we demonstrate the emergence of semantically distinct violent and nonviolent trial genres. We show that although in the late 18th century the semantic content of trials for violent offenses is functionally indistinguishable from that for nonviolent ones, a long-term, secular trend drives the system toward increasingly clear distinctions between violent and nonviolent acts. We separate this process into the shifting patterns that drive it, determine the relative effects of bureaucratic change and broader cultural shifts, and identify the synonym sets most responsible for the eventual genre distinguishability. This work provides a new window onto the cultural and institutional changes that accompany the monopolization of violence by the state, described in qualitative historical analysis as the civilizing process

    Interlocutors-Related and Hearer-Specific Causes of Misunderstanding: Processing Strategy, Confirmation Bias and Weak Vigilance

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    Noises, similarities between words, slips of the tongue, ambiguities, wrong or false beliefs, lexical deficits, inappropriate inferences, cognitive overload, non-shared knowledge, topic organisation or focusing problems, among others, may cause misunderstanding. While some of these are structural factors, others pertain to the speaker or to both the speaker and the hearer. In addition to stable factors connected with the interlocutors′ communicative abilities, cultural knowledge or patterns of thinking, other less stable factors, such as their personal relationships, psychological states or actions motivated by physiological functions, may also result in communicative problems. This paper considers a series of further factors that may eventually lead to misunderstanding, and which solely pertain to the hearer: processing strategy, confirmation bias and weak vigilance

    This Just In: Fake News Packs a Lot in Title, Uses Simpler, Repetitive Content in Text Body, More Similar to Satire than Real News

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    The problem of fake news has gained a lot of attention as it is claimed to have had a significant impact on 2016 US Presidential Elections. Fake news is not a new problem and its spread in social networks is well-studied. Often an underlying assumption in fake news discussion is that it is written to look like real news, fooling the reader who does not check for reliability of the sources or the arguments in its content. Through a unique study of three data sets and features that capture the style and the language of articles, we show that this assumption is not true. Fake news in most cases is more similar to satire than to real news, leading us to conclude that persuasion in fake news is achieved through heuristics rather than the strength of arguments. We show overall title structure and the use of proper nouns in titles are very significant in differentiating fake from real. This leads us to conclude that fake news is targeted for audiences who are not likely to read beyond titles and is aimed at creating mental associations between entities and claims.Comment: Published at The 2nd International Workshop on News and Public Opinion at ICWS

    An agent-driven semantical identifier using radial basis neural networks and reinforcement learning

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    Due to the huge availability of documents in digital form, and the deception possibility raise bound to the essence of digital documents and the way they are spread, the authorship attribution problem has constantly increased its relevance. Nowadays, authorship attribution,for both information retrieval and analysis, has gained great importance in the context of security, trust and copyright preservation. This work proposes an innovative multi-agent driven machine learning technique that has been developed for authorship attribution. By means of a preprocessing for word-grouping and time-period related analysis of the common lexicon, we determine a bias reference level for the recurrence frequency of the words within analysed texts, and then train a Radial Basis Neural Networks (RBPNN)-based classifier to identify the correct author. The main advantage of the proposed approach lies in the generality of the semantic analysis, which can be applied to different contexts and lexical domains, without requiring any modification. Moreover, the proposed system is able to incorporate an external input, meant to tune the classifier, and then self-adjust by means of continuous learning reinforcement.Comment: Published on: Proceedings of the XV Workshop "Dagli Oggetti agli Agenti" (WOA 2014), Catania, Italy, Sepember. 25-26, 201
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