Trust Estimation of Real-Time Social Harm Events

Indiana University-Purdue University Indianapolis (IUPUI)Social harm involves incidents resulting in physical, financial, and emotional hardships such as crime, drug overdoses and abuses, traffic accidents, and suicides. These incidents require various law-enforcement and emergency responding agencies to coordinate together for mitigating their impact on the society. With the advent of advanced networking and computing technologies together with data analytics, law-enforcement agencies and people in the community can work together to proactively reduce social harm. With the aim of effectively mitigating social harm events in communities, this thesis introduces a distributed web application, Community Data Analytic for Social Harm (CDASH). CDASH helps in collecting social harm data from heterogenous sources, analyzing the data for predicting social harm risks in the form of geographic hotspots and conveying the risks to law-enforcement agencies. Since various stakeholders including the police, community organizations and citizens can interact with CDASH, a need for a trust framework arises, to avoid fraudulent or mislabeled incidents from misleading CDASH. The enhanced system, called Trusted-CDASH (T-CDASH), superimposes a trust estimation framework on top of CDASH. This thesis discusses the importance and necessity of associating a degree of trust with each social harm incident reported to T-CDASH. It also describes the trust framework with different trust models that can be incorporated for assigning trust while examining their impact on prediction accuracy of future social harm events. The trust models are empirically validated by running simulations on historical social harm data of Indianapolis metro area

Social Media and Collective Intelligence: Ongoing and Future Research Streams

The tremendous growth in the use of Social Media has led to radical paradigm shifts in the ways we communicate, collaborate, consume, and create information. Our focus in this special issue is on the reciprocal interplay of Social Media and Collective Intelligence. We therefore discuss constituting attributes of Social Media and Collective Intelligence, and we structure the rapidly growing body of literature including adjacent research streams such as Social Network Analysis, Web Science, and Computational Social Science. We conclude by making propositions for future research where in particular the disciplines of artificial intelligence, computer science, and information systems can substantially contribute to the interdisciplinary academic discourse

Public Services 2.0: The Impact of Social Computing on Public Services

This report presents the findings of the study on "Public Services 2.0: The Impact of Social Computing on Public Services" conducted by TNO and DTI on behalf of IPTS from 2008 to 2009. The report gives an overview of the main trends of Social Computing, in the wider context of an evolving public sector, and in relation to relevant government trends and normative policy visions on future public services within and across EU Member States. It then provides an exhaustive literature review of research and practice in the area of Social Computing and identifies its key impact areas in the public sector. The report goes on to discuss four case studies of Social Computing-enabled communities in different areas: education (Connexions), health (Doctors.net.uk), inclusion (PatientsLikeMe) and governance (Wikileaks). This is followed by the findings of a scenario-building exercise in which two alternative scenarios were developed and related future opportunities and risks discussed. Additionally, the report presents the results of a cross-case analysis and an ad-hoc online survey which identifies the level of usage, the general characteristics and the key drivers of Social Computing for public services. The report concludes with a summary of research challenges and policy-relevant recommendations. Evidence from the study indicates that Social Computing technologies, applications and values have already been adopted in many areas of government activity. Social Computing affects several aspects of public service, related to both the front office (citizen-government relations) and the back office activities of public administrations. Social Computing is leading to new forms of ICT-enabled participation, capable of enhancing users¿ social awareness and involvement. Social Computing is also transforming relationships and ways of working within and between public sector organisations and opens the way to innovative service delivery mechanisms.JRC.J.4-Information Societ

UM SISTEMA COLABORATIVO BASEADO EM INTELIGÊNCIA COLETIVA E RECONHECIMENTO DE OBJETOS DE LOCAIS PÚBLICOS E TURÍSTICOS

Este trabalho propõe um sistema colaborativo para favorecer aos consumidores de locais públicos e turísticos acesso à informação histórica e cultural sobre os objetos que compõe esses locais. Com esse sistema colaborativo é possível por meio de um aplicativo móvel obter a imagem de um objeto de um local público e turístico, e a enviar a um WebService, que realiza a detecção e reconhecimento, e compartilha as informações históricas e culturais referente ao objeto destacado na imagem. Para isso, o Sistema colaborativo faz uso do algoritmo SIFT e RANSAC e utiliza os conceitos da inteligência coletiva no compartilhamento das informações históricas e culturais. Foram realizados experimentos com imagens de objetos de locais públicos e turísticos para comprovar a metodologia proposta

Information Systems for “Wicked Problems” – Proposing Research at the Intersection of Social Media and Collective Intelligence

The objective of this commentary is to propose some fruitful research direction built upon the reciprocal interplay of social media and collective intelligence. We focus on “wicked problems” — a class of what Introne et al. 2013 call “problems for which no single computational formulation of the problem is sufficient, for which different stakeholders do not even agree on what the problem really is, and for which there are no right or wrong answers, only answers that are better or worse from different points of view”. We argue that information systems research in particular can aid in designing appropriate systems due to benefits derived from the combined perspectives of both social media and collective intelligence. We document the relevance and timeliness of social media and collective intelligence for business and information systems engineering, pinpoint needed functionality of information systems for wicked problems, describe related research challenges, highlight prospective suitable methods to tackle those challenges, and review examples of initial results

A Graph Database Representation of Portuguese Criminal-Related Documents

Organizations have been challenged by the need to process an increasing amount of data, both structured and unstructured, retrieved from heterogeneous sources. Criminal investigation police are among these organizations, as they have to manually process a vast number of criminal reports, news articles related to crimes, occurrence and evidence reports, and other unstructured documents. Automatic extraction and representation of data and knowledge in such documents is an essential task to reduce the manual analysis burden and to automate the discovering of names and entities relationships that may exist in a case. This paper presents SEMCrime, a framework used to extract and classify named-entities and relations in Portuguese criminal reports and documents, and represent the data retrieved into a graph database. A 5WH1 (Who, What, Why, Where, When, and How) information extraction method was applied, and a graph database representation was used to store and visualize the relations extracted from the documents. Promising results were obtained with a prototype developed to evaluate the framework, namely a name-entity recognition with an F-Measure of 0.73, and a 5W1H information extraction performance with an F-Measure of 0.65

Designing a Mobile Crowdsourcing System for Campus Safety

Safety on college campuses remains a dire issue. Current reporting methods are still cumbersome and include no enhancing social aspect. Given the unique opportunity that universities are required to publish their safety report logs, we conducted a preliminary data analysis of a university's safety report log. The analysis allowed us to detect relevant trends in reporting behavior, specifically pertaining to where, when, and how soon the community would report safety incidents. Motivated by these findings and by literature promoting interactive reporting systems, we designed a novel mobile app which aims to enable the spread of crowdsourced public safety information. This app allows for immediate mass sharing of self-reported safety incidents, as well as the opportunity for witness reporting. Feedback from a paper prototype interview study indicated that these qualities would facilitate increased interactivity among its user community, and ultimately promote awareness of campus safety.ye