Query: Information  process model    bullying

title: Adolescents and Cyber Bullying: The Precaution Adoption Process Model
abstract: A survey of adolescents (N 1,488) documented Facebook use and experience with cyber bullying. The study found that 84 of adolescents (middle school through college undergraduates) use Facebook, and that most users log on daily. While 30 of the sample reported being cyber bullied, only 12.5 quit using the site, and only 18 told a parent or school official about the abuse. Up to 75 of middle school Facebook users have experienced cyber bullying. The current study was the first to apply the Precaution Adoption Process Model (PAPM) to cyber bullying or to test the model with children and adolescents. Results suggest that most adolescents are aware of cyber bullying and acknowledge it as a problem in their school. About half of the adolescents did not progress beyond Stage 2 of the PAPM (aware of the problem, but haven't really thought about it) Adolescents also exhibited optimistic bias, believing they were less likely than peers to become cyber bullied. Implications for prevention education are discussed.

title: Unsupervised Cyberbullying Detection via Time Informed Gaussian Mixture Model
abstract: Social media is a vital means for information sharing due to its easy access, low cost, and fast dissemination characteristics. However, increases in social media usage have corresponded with a rise in the prevalence of cyberbullying. Most existing cyberbullying detection methods aresupervised and, thus, have two key drawbacks: (1) The data labeling process is often time consuming and labor intensive; (2) Current labeling guidelines may not be generalized to future instances because of different language usage and evolving social networks. To address these limitations, this work introduces a principled approach forunsupervised cyberbullying detection. The proposed model consists of two main components: (1) Arepresentation learning network that encodes the social media session by exploiting multi modal features, e.g. text, network, and time. (2) Amulti task learning network that simultaneously fits the comment inter arrival times and estimates the bullying likelihood based on a Gaussian Mixture Model. The proposed model jointly optimizes the parameters of both components to overcome the shortcomings of decoupled training. Our core contribution is an unsupervised cyberbullying detection model that not only experimentally outperforms the state of the art unsupervised models, but also achieves competitive performance compared to supervised models.

title: Automation in Social Networking Comments With the Help of Robust fastText and CNN
abstract: Social networking and online conversation platforms provide us with the power to share our views and ideas. However, nowadays on social media platforms, many people are taking these platforms for granted, they see it as an opportunity to harass and target others leading to cyber attack and cyber bullying which lead to traumatic experiences and suicidal attempts in extreme cases. Manually identifying and classifying such comments is a very long, tiresome and unreliable process. To solve this challenge, we have developed a deep learning system which will identify such negative content on online discussion platforms and successfully classify them into proper labels. Our proposed model aims to apply the text based Convolution Neural Network (CNN) with word embedding, using fastText word embedding technique. fastText has shown efficient and more accurate results compared to Word2Vec and GLOVE model. Our model aims to improve detecting different types of toxicity to improve the social media experience. Our model classifies such comments in six classes which are Toxic, Severe Toxic, Obscene, Threat, Insult and Identity hate. Multi Label Classification helps us to provide an automated solution for dealing with the toxic comments problem we are facing.

title: Belittling the Source: Trustworthiness Indicators to Obfuscate Fake News on the Web
abstract: With the growth of the internet, the number of fake news online has been proliferating every year. The consequences of such phenomena are manifold, ranging from lousy decision making process to bullying and violence episodes. Therefore, fact checking algorithms became a valuable asset. To this aim, an important step to detect fake news is to have access to a credibility score for a given information source. However, most of the widely used Web indicators have either been shut down to the public (e.g. Google PageRank) or are not free for use (Alexa Rank) Further existing databases are short manually curated lists of online sources, which do not scale. Finally, most of the research on the topic is theoretical based or explore confidential data in a restricted simulation environment. In this paper we explore current research, highlight the challenges and propose solutions to tackle the problem of classifying websites into a credibility scale. The proposed model automatically extracts source reputation cues and computes a credibility factor, providing valuable insights which can help in belittling dubious and confirming trustful unknown websites. Experimental results outperform state of the art in the 2 classes and 5 classes setting.

title: The right to be included: Ensuring the inclusive learning and work environment for people with disabilities in academia
abstract: In the spirit of the growing Time is Up movement in North America, this paper aims to focus on the human dimension of academic learning environments and delves into the reasons for the continuous oppression, discrimination and bullying (ODB) of faculty members with disabilities in academia, showing the particularly detrimental effect of ODB in the small professionally oriented field of information science.,The conceptualizing of continuous ODB of people with disabilities in academia is done by carefully scrutinizing the state of affairs; presenting a nuanced survey of utilized terminology; providing a new and inclusive definition of everyday oppression; introducing a new model of an oppressive workplace environment experienced by people with disabilities; showing the centrality of information behaviours and phenomena in ODB; highlighting the high relevance of this discussion to learning science; and outlining potential detrimental effects of ODB on the psychological climate in and the process of professional higher education.,The model of an oppressive workplace environment experienced by people with disabilities is presented.,Unlike previous models of ODB at the workplace, the current model puts information phenomena as decisive factors in continuous ODB against people with disabilities; particular attention is paid to information avoidance behaviours; distorted or delayed information messages transmitted by managers to employees; gossip as an informal information based tactic of ODB; the insufficient protection of privacy and confidentiality of information about disabilities and personal health; and vague information messages that diminish the usefulness of university policies on disabilities.

title: Open class authorship attribution of lithuanian internet comments using one class classifier
abstract: Internet can be misused by cyber criminals as a platform to conduct illegitimate activities (such as harassment, cyber bullying, and incitement of hate or violence) anonymously. As a result, authorship analysis of anonymous texts in Internet (such as emails, forum comments) has attracted significant attention in the digital forensic and text mining communities. The main problem is a large number of possible of authors, which hinders the effective identification of a true author. We interpret open class author attribution as a process of expert recommendation where the decision support system returns a list of suspected authors for further analysis by forensics experts rather than a single prediction result, thus reducing the scale of the problem. We describe the task formally and present algorithms for constructing the suspected author list. For evaluation we propose using a simple Winner Takes All (WTA) metric as well as a set of gain discount model based metrics from the information retrieval domain (mean reciprocal rank, discounted cumulative gain and rank biased precision) We also propose the List Precision (LP) metric as an extension of WTA for evaluating the usability of the suspected author list. For experiments, we use our own dataset of Internet comments in Lithuanian language and consider the use of language specific (Lithuanian) lexical features together with general lexical features derived from English language. For classification we use one class Support Vector Machine (SVM) classifier. The results of experiments show that the usability of open class author attribution can be improved considerably by using a set of language specific lexical features together with general lexical features, while the proposed method can be used to reduce the number of suspected authors thus alleviating the work of forensic linguists.

title: Using the extended parallel process model to examine teachers' likelihood of intervening in bullying.
abstract: Teachers play a critical role in protecting students from harm in schools, but little is known about their attitudes toward addressing problems like bullying. Previous studies have rarely used theoretical frameworks, making it difficult to advance this area of research. Using the Extended Parallel Process Model (EPPM) we examined the association between teachers' perceived threat and perceived efficacy and their likelihood of intervening in bullying situations. We also explored whether the school level at which teachers taught (elementary vs secondary) and their years of experience of working at the school moderated these associations.  Data come from 1062 teachers who completed an anonymous Web based survey regarding their attitudes and responses to bullying. Structural equation modeling and multiple group analyses were used to test the hypothesized relationships and for effect modification by teacher characteristics.  Perceived threat and efficacy were associated with teachers' likelihood of intervening in bullying situations but varied based on teachers' years of experience at their school. For less experienced teachers, perceived efficacy, but not perceived threat, was strongly associated with likelihood of intervening. For more experienced teachers, both perceived threat and perceived efficacy were significantly associated. Finally, the associations did not differ by the school level.  This is one of few studies examining possible predictors of teachers' likelihood of intervening in bullying situations. EPPM may inform the development of bullying interventions aiming to increase the likelihood that teachers will intervene in bullying situations.

title: The role of work stressors, coping strategies and coping resources in the process of workplace bullying: A systematic review and development of a comprehensive model
abstract: Both work and person related factors may trigger workplace bullying. Work related factors, such as role stressors, can create a stressful work environment leading to bullying. Additionally, person related factors, such as emotion focused coping, could make employees more vulnerable to bullying. In this study, we aimed to develop a comprehensive model integrating these factors. We systematically reviewed studies published between 1984 and 2014. First, we identified the most relevant work related stressors (role conflict, workload, role ambiguity, job insecurity and cognitive demands) as predictors of being a target of workplace bullying. Second, problem focused and emotion focused coping strategies that may moderate the association between stressors and targets of bullying were identified. Third, coping resources that are associated with coping strategies were indicated. Results suggested a model in which reappraisal coping, confrontive coping, practical coping, direct coping, active coping, social support (problem focused coping) and self care (emotion focused coping) decrease the association between work stressors and bullying (i.e. buffer effect) Wishful thinking, emotional coping, avoidance, recreation, social support and suppression (emotion focused coping) increase this association (i.e. boost effect) Coping resources (locus of control, self efficacy, optimism, co workers support, supervisor support, task complexity, participation in decision making, autonomy and continuance commitment) related positively to problem focused coping strategies and negatively to emotion focused coping strategies.

title: Perceived school climate and adolescents' bullying perpetration: A moderated mediation model of moral disengagement and peers' defending
abstract: This research examined whether moral disengagement mediated the association between adolescents' perceived school climate and bullying perpetration, and this mediating process was moderated by peers' defending. Participants were 404 Chinese adolescents. Results indicated that adolescents who perceive a positive school climate were less likely to bully others and moral disengagement mediated this relationship, even after controlling for adolescents' gender, age, defending, perspective taking, and empathic concern. Furthermore, peers' defending moderated the direct and indirect associations between adolescents' perceived school climate and bullying perpetration through moral disengagement. This indirect association was moderated by peers' defending in the first stage of the mediation process, such that the association between perceived school climate and moral disengagement became nonsignificant for adolescents with high peers' defending. The direct association between perceived school climate and bullying perpetration surprisingly became nonsignificant for adolescents with low peers' defending. This study contributes to research clarifying the mediating and moderating mechanisms underlying the beneficial effect of adolescents' perceived school climate on bullying perpetration.

title: Workplace bullying and employee outcomes: a moderated mediated model
abstract: This paper investigates the relationship between workplace bullying and employee outcomes in a healthcare setting. Drawing on HR process theory, we investigate the mediating role of the perceived effectiveness of implementation of anti bullying practices on employee outcomes and whether targeted line manager training was a moderator of that relationship. Our multi level analysis (utilising responses from 1507 employees within 47 hospitals with matched HR Director interviews) finds that the relationship between workplace bullying and employee outcomes is partially mediated by employees' perceived effective implementation of intended anti bully practices. The mediated relationship is moderated by targeted line manager training in anti bullying practices. The mediated moderation model illustrates that it is effective implementation of anti bullying practices enhanced by targeted training that is required to reduce bullying probabilities and their associated negative employee outcomes. The paper contributes to resource based view of the firm, HR process and human capital theories. The implications for future research and practice are discussed.