21,596 research outputs found

    Triaging Content Severity in Online Mental Health Forums

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    Mental health forums are online communities where people express their issues and seek help from moderators and other users. In such forums, there are often posts with severe content indicating that the user is in acute distress and there is a risk of attempted self-harm. Moderators need to respond to these severe posts in a timely manner to prevent potential self-harm. However, the large volume of daily posted content makes it difficult for the moderators to locate and respond to these critical posts. We present a framework for triaging user content into four severity categories which are defined based on indications of self-harm ideation. Our models are based on a feature-rich classification framework which includes lexical, psycholinguistic, contextual and topic modeling features. Our approaches improve the state of the art in triaging the content severity in mental health forums by large margins (up to 17% improvement over the F-1 scores). Using the proposed model, we analyze the mental state of users and we show that overall, long-term users of the forum demonstrate a decreased severity of risk over time. Our analysis on the interaction of the moderators with the users further indicates that without an automatic way to identify critical content, it is indeed challenging for the moderators to provide timely response to the users in need.Comment: Accepted for publication in Journal of the Association for Information Science and Technology (2017

    The Transport Problems of Inner City Firms: An Approach to Solutions.

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    The paper arises from a recent investigation into the extent to which transport problems affect manufacturing firms and their employees. It summarises the conclusions of that study and notes their implications for the selection and assessment of transport policies designed to assist industry. One of the conclusions is that most problems are local or site- specific; this suggests that local and probably low cost solutions developed by local authorities or by firms themselves may well be more appropriate than programmes of major investment. However, another conclusion is that firms are generally inadequately aware of the effects of their transport problems and the costs to which they give rise; this suggests that the justification even for low cost solutions may not be being made sufficiently apparent to local authorities. These conclusions indicate the need for a more careful assessment of the effects of both high and low cost transport policies on industry. The paper outlines the way in which an analysis of firms' transport problems may be used to develop appropriate solutions and to assess their effects. It discusses some of the problems of such an investigation, using case studies drawn from recent research in Inner London

    Lexical Features in Coreference Resolution: To be Used With Caution

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    Lexical features are a major source of information in state-of-the-art coreference resolvers. Lexical features implicitly model some of the linguistic phenomena at a fine granularity level. They are especially useful for representing the context of mentions. In this paper we investigate a drawback of using many lexical features in state-of-the-art coreference resolvers. We show that if coreference resolvers mainly rely on lexical features, they can hardly generalize to unseen domains. Furthermore, we show that the current coreference resolution evaluation is clearly flawed by only evaluating on a specific split of a specific dataset in which there is a notable overlap between the training, development and test sets.Comment: 6 pages, ACL 201

    The impact of face-to-face street fundraising on organizational reputation

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    Although many stakeholders perceive face-to-face street fundraising as unpleasant, nonprofit managers encourage it as a way to attract donors. To understand the long-term effects of this fundraising method, we used a mixed-methods experimental design to investigate how face-to-face street fundraising affects organizational reputation and stakeholder support intentions in comparison with letter fundraising. The findings reveal that face-to-face street fundraising has a significant negative influence on the stakeholders' perceptions of an organization. Further, qualitative datashow that the negative perception originates primarily from perceived pressure, distrust, and obtrusion, which are triggered by face-to-face street fundraising. Our studythus reveals long-term reputational consequences that nonprofit organizations should consider before deciding on fundraising methods

    Malware detection techniques for mobile devices

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    Mobile devices have become very popular nowadays, due to its portability and high performance, a mobile device became a must device for persons using information and communication technologies. In addition to hardware rapid evolution, mobile applications are also increasing in their complexity and performance to cover most needs of their users. Both software and hardware design focused on increasing performance and the working hours of a mobile device. Different mobile operating systems are being used today with different platforms and different market shares. Like all information systems, mobile systems are prone to malware attacks. Due to the personality feature of mobile devices, malware detection is very important and is a must tool in each device to protect private data and mitigate attacks. In this paper, analysis of different malware detection techniques used for mobile operating systems is provides. The focus of the analysis will be on the to two competing mobile operating systems - Android and iOS. Finally, an assessment of each technique and a summary of its advantages and disadvantages is provided. The aim of the work is to establish a basis for developing a mobile malware detection tool based on user profiling.Comment: 11 pages, 6 figure
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