In online discussion communities, users can interact and share information and opinions on a wide variety of topics. However, some users may create multiple identities, or sockpuppets, and engage in undesired behavior by deceiving others or manipulating discussions. In this work, we study sockpuppetry across nine discussion communities, and show that sockpuppets differ from ordinary users in terms of their posting behavior, linguistic traits, as well as social network structure. Sockpuppets tend to start fewer discussions, write shorter posts, use more personal pronouns such as I'', and have more clustered ego-networks. Further, pairs of sockpuppets controlled by the same individual are more likely to interact on the same discussion at the same time than pairs of ordinary users. Our analysis suggests a taxonomy of deceptive behavior in discussion communities. Pairs of sockpuppets can vary in their deceptiveness, i.e., whether they pretend to be different users, or their supportiveness, i.e., if they support arguments of other sockpuppets controlled by the same user. We apply these findings to a series of prediction tasks, notably, to identify whether a pair of accounts belongs to the same underlying user or not. Altogether, this work presents a data-driven view of deception in online discussion communities and paves the way towards the automatic detection of sockpuppets.
A hydraulic control system for use in an automatic transmission including a fluid coupling type torque converter, and a gear system provided with two or more frictional engaging devices adapted to establish two or more speed conditions. The hydraulic system further includes a hydraulic pressure source, a line pressure control valve for supplying a regulated line pressure, by receiving a hydraulic pressure from the hydraulic pressure source, a throttle pressure control valve for generating a throttle pressure commensurate with an intake throttle opening, a governor pressure control valve for generating a governor pressure commensurate with vehicle speed, a manual change-over valve for enabling manual change-over of the transmission, two or more shift valves for shifting the path of the line pressure to be supplied to the frictional engaging devices in response to abalancing of the relationship between the throttle pressure and the governor pressure, the shift valves including one shift valve operative to establish the highest speed ratio for the transmission, and a highest speed control device for controlling to a low-speed-side shift position the one shift valve of the aforementioned shift valves which is operative to establish the highest speed ratio irrespective of the governor pressure resulting when the intake throttle opening remains over a given valve.  This paper presents preliminary results of using authorship attribution methods for the detection of sockpuppeteering in Wikipedia. Sockpuppets are fake accounts created by malicious users to bypass Wikipedia’s regulations. Our dataset is composed of the comments made by the editors on the talk pages. To overcome the limitations of the short lengths of these comments, we use an voting scheme to combine predictions made on individual user entries. We show that this approach is promising and that it can be a viable alternative to the current human process that Wikipedia uses to resolve suspected sockpuppet cases. This research has three goals: first, to find out how prevalent online deception is within a sample of Israeli users, second, to explore the underlying motivations to deceive online, and third, to discover the emotions that accompany online deception. A web-based survey was distributed in 14 discussion groups, and the answers of 257 respondents were analyzed. It was found that, while most of the respondents believe that online deception is very widespread, only about one-third of them reported engaging in online deception. Frequent users deceive online more than infrequent users, young users more than old, and competent users more than non-competent. The most common motivations to deceive online were "play" on the one hand and privacy concerns on the other. Most people felt a sense of enjoyment while engaging in online deception. The results are discussed in light of a possible mechanism for changing personal moral standards.   Multiple identity systems involve a physical self and a set of virtual identities.An 8-item model of avatar functions within a multiple identity system was identified.The vast majority of participants noted all or most functions in their interviews.The combined physical and virtual selves form a wider system of personality. Prior research has shown that approximately 50 of active participants in the 3D virtual world of Second Life have one or more secondary avatars or "alts" in addition to their primary avatar. Thus, these individuals are operating a "multiple or poly-identity system" composed of a physical self, a primary avatar, and one or more alts. However, little is known about the functions these virtual identities serve for the virtual-world user. The current study involved qualitative analysis of semistructured interviews with Second Life participants (N=24) who had a primary avatar and at least one alt. Interviews were coded to examine the functions that primary avatars and alts served. Eight functions-seven suggested by previous research on virtual world identity and one that emerged from analyses-were reflected in a large majority of the transcribed interviews and are described in the article. The current findings add to our understanding of how multifaceted identity systems operate, as more individuals augment their physical self with a set of virtual identities. In digital forensics, questions often arise about the authors of documents: their identity, demographic background, and whether they can be linked to other documents. The field of stylometry uses linguistic features and machine learning techniques to answer these questions. While stylometry techniques can identify authors with high accuracy in non-adversarial scenarios, their accuracy is reduced to random guessing when faced with authors who intentionally obfuscate their writing style or attempt to imitate that of another author. While these results are good for privacy, they raise concerns about fraud. We argue that some linguistic features change when people hide their writing style and by identifying those features, stylistic deception can be recognized. The major contribution of this work is a method for detecting stylistic deception in written documents. We show that using a large feature set, it is possible to distinguish regular documents from deceptive documents with 96.6 accuracy (F-measure). We also present an analysis of linguistic features that can be modified to hide writing style.