Don Fallis and Andreas Stokke propose that the classical definition of lying is inadequate due to the insistence on deceptive doxastic goals. Such goals have been proven problematic in the light of baldface lying. Both Fallis and Stokke argue that baldface lying are actual instances of lying and that a valid definition of lying should therefore include these. They suggest that lies be understood in a pragmatic framework and ground their definitions in the linguistic tradition following Paul Grice and Robert Stalnaker, respectively. Lies are to be understood as conscious breaches of pragmatic maxims. In this essay I show that Fallis project fails due to limitations inherent to Grice theory of communication. Andreas Stokke definition, on the other hand, building on the work of Jonathan Cohen and Robert Stalnaker, turns out to be a beautiful explication of the classical definition of lying – that besides managing the extensional problem that baldface lies pose also succeeds in making them intelligible epistemically. However, I argue that his categorical rejection of a necessary deceptive condition is refuted by his own definition and theoretical build up. Contrary to Stokke’s own conviction, I thus maintain that his contribution be understood as a significant vindication of the deceptive theory of lying. Finally, lies told by young children seem to pose as great a problem for non-deceptive theories of lying as baldface lies did for deceptive theories.

No description available.

No description available.

No description available.

In today's world, online communication through social network services (SNSs) has become an essential aspect of people's daily lives. As social networking sites (SNSs) have become more sophisticated, cyber attackers have found ways to exploit them for harmful activities such as financial fraud, privacy violations, and sexual or labor exploitation. Thus, it is imperative to gain an understanding of these activities and develop effective countermeasures to build SNSs that can be trusted. The existing approaches have focused on discussing detection mechanisms for a particular type of online social deception (OSD) using various artificial intelligence (AI) techniques, including machine/deep learning (ML/DL) or text mining. However, fewer studies exist on the prevention and response (or mitigation) mechanisms for effective defense against OSD attacks. Further, there have been insufficient efforts to investigate the underlying intents and tactics of those OSD attackers through their in-depth understanding. This dissertation is motivated to take defense approaches to combat OSD attacks through the in-depth understanding of the psychological-social behaviors of attackers and potential victims, which can effectively guide us to take more proactive action against OSD attacks which can minimize potential damages to the potential victims as well as be cost-effective by minimizing or saving recovery cost. In this dissertation, we examine the OSD attacks mainly through two tasks, including understanding their causes and combating them in terms of prevention, detection, and mitigation. In the OSD understanding task, we investigate the intent and tactics of false informers (e.g., fake news spreaders) in propagating fake news or false information. We understand false informers' intent more accurately based on intent-related phrases from fake news contexts to decide on effective and efficient defenses (or interventions) against them. In the OSD combating task, we develop the defense systems following two sub-tasks: (1) The social capital-based friending recommendation system to guide OSN users to choose trustworthy users to defend against phishing attackers proactively; and (2) The defensive opinion update framework for OSN users to process their opinions by filtering out false information. The schemes proposed for combating OSD attacks contribute to the prevention, detection, and mitigation of OSD attacks. / Doctor of Philosophy / This Ph.D. dissertation explores the issue of online social deception (OSD) in the context of social networking services (SNSs). With the increasing sophistication of SNSs, cyber attackers have found ways to exploit them for harmful activities, such as financial fraud and privacy violations. While previous studies have focused on detection mechanisms using artificial intelligence (AI) techniques, this dissertation takes a defense approach by investigating the underlying psychological-social behaviors of attackers and potential victims. Through two tasks of understanding OSD causes and combating them through various AI approaches, this dissertation proposes a social capital-based friending recommendation system, a defensive opinion update framework, and a fake news spreaders' intent analysis framework to guide SNS users in choosing trustworthy users and filtering out phishing attackers or false information. The proposed schemes contribute to the prevention, detection, and mitigation of OSD attacks, potentially minimizing potential damages to potential victims and saving recovery costs.

This research paper has examined the validity of the Forensic Assessment Interview Technique (FAINT). FAINT is a specific interview process - accepted and in current use - integrating the works of this researcher with the works of John Reid, Richard Arther, and Avinoam Sapir. The FAINT technique involves the evaluation of nonverbal behavior, projective analysis of unwitting verbal cues, and statement analysis. The fundamental hypothesis of FAINT is that truthful and deceptive criminal suspects differ demonstrably in their nonverbal, verbal and written communication, when asked to respond to a structured format of interview questions. FAINT maintains that these differences are observable and can be quantified to allow forensic interviewers to make accurate determinations of a suspect's involvement in a crime. This research has examined the validity of the technique as measured by a traditional, unweighted 3 point scale and a weighted scoring system (an issue being researched in this paper) comparatively used for determining truth or deception. This dissertation reports the results of both scoring systems, as well as a comparison between them and the historically used Behavioral Analysis Interview (BAI) that was developed by John E. Reid. / Criminology / MA (Criminology)

This dissertation is a study of appetite in Plato’s Timaeus, Republic and Phaedrus. In recent research is it often suggested that Plato considers appetite (i) to pertain to the essential needs of the body, (ii) to relate to a distinct set of objects, e.g. food or drink, and (iii) to cause behaviour aiming at sensory pleasure. Exploring how the notion of appetite, directly and indirectly, connects with Plato’s other purposes in these dialogues, this dissertation sets out to evaluate these ideas. By asking, and answering, three philosophically and interpretatively crucial questions, individually linked to the arguments of the dialogues, this thesis aims to show (i) that the relationship between appetite and the body is not a matter of survival, and that appetite is better understood in terms of excess; (ii) that appetite is multiform and cannot be defined in terms of a distinct set of objects; and (iii) that appetite, in Plato, can also pertain to non-sensory objects, such as articulated discourse. Chapter one asks what the universe can teach us about embodied life. It argues that Plato, in the Timaeus, works with an important link between the universe and the soul, and that the account of disorder, irrationality and multiformity identifying a pre-cosmic condition of the universe provides a key to understanding the excessive behaviour and condition of a soul dominated by appetite. Chapter two asks why the philosophers of the Republic’s Kallipolis return to the cave, and suggests that Plato’s notion of the noble lie provides a reasonable account of this. By exploring the Republic’s ideas of education, poetry and tradition, it argues that appetite – a multiform and appearance oriented source of motivation – is an essential part of this account. Chapter three asks why Socrates characterizes the speeches of the Phaedrus as deceptive games. It proposes that this question should be understood in the light of two distinctions: one between playful and serious discourse and one between simple and multiform. It argues that the speeches of the Phaedrus are multiform games, and suggests that appetite is the primary source of motivation of the soul addressed, personified by Phaedrus.

Universiẗat, Diss., 2004--Regensburg.

This research paper has examined the validity of the Forensic Assessment Interview Technique (FAINT). FAINT is a specific interview process - accepted and in current use - integrating the works of this researcher with the works of John Reid, Richard Arther, and Avinoam Sapir. The FAINT technique involves the evaluation of nonverbal behavior, projective analysis of unwitting verbal cues, and statement analysis. The fundamental hypothesis of FAINT is that truthful and deceptive criminal suspects differ demonstrably in their nonverbal, verbal and written communication, when asked to respond to a structured format of interview questions. FAINT maintains that these differences are observable and can be quantified to allow forensic interviewers to make accurate determinations of a suspect's involvement in a crime. This research has examined the validity of the technique as measured by a traditional, unweighted 3 point scale and a weighted scoring system (an issue being researched in this paper) comparatively used for determining truth or deception. This dissertation reports the results of both scoring systems, as well as a comparison between them and the historically used Behavioral Analysis Interview (BAI) that was developed by John E. Reid. / Criminology and Security Science / MA (Criminology)

Financial fraud rampages onwards seemingly uncontained. The annual cost of fraud in the UK is estimated to be as high as £193bn a year [1] . From a data science perspective and hitherto less explored this thesis demonstrates how the use of linguistic features to drive data mining algorithms can aid in unravelling fraud. To this end, the spotlight is turned on Financial Statement Fraud (FSF), known to be the costliest type of fraud [2]. A new corpus of 6.3 million words is composed of102 annual reports/10-K (narrative sections) from firms formally indicted for FSF juxtaposed with 306 non-fraud firms of similar size and industrial grouping. Differently from other similar studies, this thesis uniquely takes a wide angled view and extracts a range of features of different categories from the corpus. These linguistic correlates of deception are uncovered using a variety of techniques and tools. Corpus linguistics methodology is applied to extract keywords and to examine linguistic structure. N-grams are extracted to draw out collocations. Readability measurement in financial text is advanced through the extraction of new indices that probe the text at a deeper level. Cognitive and perceptual processes are also picked out. Tone, intention and liquidity are gauged using customised word lists. Linguistic ratios are derived from grammatical constructs and word categories. An attempt is also made to determine ‘what’ was said as opposed to ‘how’. Further a new module is developed to condense synonyms into concepts. Lastly frequency counts from keywords unearthed from a previous content analysis study on financial narrative are also used. These features are then used to drive machine learning based classification and clustering algorithms to determine if they aid in discriminating a fraud from a non-fraud firm. The results derived from the battery of models built typically exceed classification accuracy of 70%. The above process is amalgamated into a framework. The process outlined, driven by empirical data demonstrates in a practical way how linguistic analysis could aid in fraud detection and also constitutes a unique contribution made to deception detection studies.