Automated Framework to Improve User?s Awareness and to Categorize Friends on Online Social Networks

The popularity of online social networks has brought up new privacy threats. These threats often arise after users willingly, but unwittingly reveal their information to a wider group of people than they actually intended. Moreover, the well adapted ?friends-based? privacy control has proven to be ill-equipped to prevent dynamic information disclosure, such as in user text posts. Ironically, it fails to capture the dynamic nature of this data by reducing the problem to manual privacy management which is time-consuming, tiresome and error-prone task. This dissertation identifies an important problem with posting on social networks and proposes a unique two phase approach to the problem. First, we suggest an additional layer of security be added to social networking sites. This layer includes a framework for natural language to automatically check texts to be posted by the user and detect dangerous information disclosure so it warns the user. A set of detection rules have been developed for this purpose and tested with over 16,000 Facebook posts to confirm the detection quality. The results showed that our approach has an 85% detection rate which outperforms other existing approaches. Second, we propose utilizing trust between friends as currency to access dangerous posts. The unique feature of our approach is that the trust value is related to the absence of interaction on the given topic. To approach our goal, we defined trust metrics that can be used to determine trustworthy friends in terms of the given topic. In addition, we built a tool which calculates the metrics automatically, and then generates a list of trusted friends. Our experiments show that our approach has reasonably acceptable performance in terms of predicting friends? interactions for the given posts. Finally, we performed some data analysis on a small set of user interaction records on Facebook to show that friends? interaction could be triggered by certain topics

The Social Media Machines: An Investigation of the Effect of Trust Moderated by Disinformation on Users’ Decision-Making Process

Social media networking sites (SMNS) have become a popular communications medium where users share information, knowledge, and persuasion. In less than two decades, social media\u27s (SM) dominance as a communication medium can\u27t be disputed, for good or evil. Combined with the newly found immediacy and pervasiveness, these SM applications\u27 persuasive power are useful weapons for organizations, angry customers, employees, actors, and activists bent on attacking or hacking other individuals, institutions, or systems. Consequently, SM has become the preferred default mechanism of news sources; however, users are unsure if the information gathered is true or false. According to the literature, SMNS generates large amounts of fake news or disinformation. The rapid proliferation of disinformation, information disseminated with the intent to harm, through SMNS has dramatically influenced and reduced people\u27s trust in the story and hints at hand. Disinformation has caused data breaches and many injured individuals and organizations, resulting in a lack of confidence in SMNS. While irrefutable that SMNS has become the new news outlet, trust remains the foundation of all communication. Since SM has changed the communication process, it is perceived as the most dangerous information dissemination vehicle known to society. Unfortunately, no one is safe from its lethality. Users must approach their usage with extreme care by understanding the technical capabilities and increasing their competence in detecting disinformation campaigns\u27 powerful influence. The continuous spread of disinformation has caused the credibility and trust of behemoths like Facebook, Twitter, and Instagram, to be significantly affected. Since trust is an essential factor in SMNS, mistrust hinders users\u27 abilities to make informed decisions. Research suggests that people make decisions based on the available information; therefore, it can be deduced that the decision-making process of SMNS users has been forever altered. Consequently, monitoring the spread of disinformation has become a front-burner priority for the government and society. By examining the effect of trust moderated by disinformation, this study aimed to investigate the factors that affect SMNS users\u27 decision-making behaviors. Factors influencing trust were also examined using the Conformity Group Norm Theory (CGNT) and Self Concept Theory (SCT). A theoretical model was created, and there were seven constructs; decision-making (DM), trust (TR), and the trust influencing factors: identification (ID), compliance (CP), internalization (IN), agency (AG), and community (CM). The theoretical model tested was based on the linear directional relationship of trust and decision making moderated by disinformation. This research tested three social media networking sites, Facebook, Twitter, and Instagram, with disinformation empirically. This quantitative study employed a role-play scenario web survey methodology and adopted a two-step Pearson r correlation coefficient procedure for data analysis. Before collecting data, an expert panel reviewed, and pilot tested the survey. The expert review recommended changes to the wording, length, and formatting of the instrument, allowing the pilot test to be easily tested by participants. The web-based scenario survey was designed with a 5- point Likert scale and distributed to SMNS users through Qualtrics XM to gather data on their decision-making process. The data analysis results revealed the moderating effect of disinformation between trust and the decision-making process of SMNS users. The data supported the conformity group norm theory (CGNT) and self-concept theory (SCT) factors. The results indicated that identification (ID), compliance (CP), internalization (IN), agency (AG), and community (CM) influence trust. Since the spread of disinformation through SMNS has much broader implications for democracy and society as a whole, this research\u27s results contribute to the knowledge of SM users\u27 behavior and decision-making processes. This study also contributes to the IS body of knowledge on social cybersecurity and has implications for practitioners and academics. This study offers a model by integrating behavioral and cognitive theories better to understand the directional relationship of trust and decision-making when exposed to disinformation. The model also identifies essential elements that influence SMNS users\u27 trust and engage them in risky cybersecurity behaviors. Furthermore, this study provides evidence of the need for future US social media governance

”Some rakentaa polkua kohti ostopäätöstä” : Tutkimus yhteisönhallinnasta yritysten Facebook-sivuilla

Yhä useammat verkkoyhteisöt ovat kaupallisten toimijoiden hallitsemia, mutta verkkoyhteisötutkimusta yritysnäkökulmasta on tehty toistaiseksi vähän. Tämä tutkimus paneutuu verkkoyhteisönhallinnan käytäntöihin ja yhteisöjohtajien työhön yritysnäkökulmasta. Tutkimuksen tavoite on selvittää, miten yritysten verkkoyhteisöjä hallitaan ja millaista yhteisöllisyyttä näissä verkkoyhteisöissä näkyy. Tutkimuksessa käydään läpi aikaisempia verkkoyhteisömääritelmiä ja yhteisöllisyyden käsitettä. Lisäksi esitellään tutkimuksessa esiintyneitä yhteisöjohtamisen käytäntöjä ja syitä verkkoyhteisötoimintaan. Aikaisemman tutkimuksen perusteella on luotu teemoja, joihin kirjallisuuskatsaus rakentuu. Näitä teemoja on hyödynnetty myös tutkimuksen empiirisessä osassa. Tutkielmaan on valittu neljä Suomessa toimivaa esimerkkiyritystä: Fazer, OP, Sinebrychoff ja Sonera. Yritysten Facebook-sivuilla on tehty kolmiosainen analyysi. Analyysissä keskitytään Facebook-sivujen sisältöihin, yhteisönhallinnan käytäntöihin sekä vuorovaikutuksen ja yhteisöllisyyden esiintymiseen. Analyysin lisäksi jokaisesta yrityksestä on haastateltu sosiaalisen median yhteisönhallinnasta vastaavaa henkilöä. Haastattelut toimivat tiedonlähteenä ja tukiaineistona Facebook-sivujen analyysille. Analyysin perusteella yhteisöjohtajien työhön katsotaan kuuluvan kanavakokonaisuuden hallintaa ja koordinoimista, sisällöntuotantoa, asiakaspalvelua ja moderointia. Esimerkkiyritykset käyttävät keskenään samoja sosiaalisen median kanavia, mutta kokeilevat rohkeasti myös uusia kanavia. Yritysten keskustelutyyli Facebook-sivuilla on ystävällistä, rentoa ja ihmisläheistä. Sisällöillä pyritään palvelemaan yhteisöjen käyttäjäryhmiä, jotka vastaavat yritysten asiakasryhmiä. Facebook-sivujen rooli viestinnässä eroaa yritysten välillä. Sivuja käytetään brändinrakennukseen, vuorovaikuttamiseen, muihin kanaviin ohjaamiseen ja asiakaspalveluun. Yhteisöjen käyttäjistä muistetaan erityisesti negatiivisesti esiintyvät ja kyseisten käyttäjien kommenttejaan saatetaan piilottaa, vaikka moderointiin suhtaudutaan muuten hellästi. Yhteisöllisyyttä esiintyy esimerkkiyritysten Facebook-sivuilla vain vähän. Tukemista ja muiden kanssa keskustelemista löytyy lähinnä negatiivisten aiheiden ympäriltä. Yritykset eivät ensisijaisesti tavoittele yhteisöllisyyden lisäämistä, vaan sivujen on tarkoitus tukea liiketoimintaa ja toimia polkuna ostopäätökselle. Sivujen käyttäjien toiminnasta päätellään, että käyttäjät hakevat sivuilta konkreettista hyötyä, kuten parempaa palvelua tai kilpailuvoittoja. Johtopäätöksissä yhteisöjohtajan roolin todetaan noudattavan vain osin kirjallisuuskatsauksessa esiintyneitä teemoja. Yhteisöjohtajat eivät panosta yhteisöllisyyden lisäämiseen, eikä sitä esiinny huomattavasti sivuilla. Yhteisöjen jäsenet eivät pyri keskustelemaan toistensa kanssa. Näiden johtopäätösten tuella tutkielma kyseenalaistaa yhteisö-sanan käytön yritysten Facebook-sivujen kohdalla. Sivujen tutkiminen yhteisönäkökulmasta on harhaanjohtavaa, koska se asettaa niille vääränlaisia odotuksia. Sivuja pitäisi tutkia ja arvioida niille asetettujen tavoitteiden valossa. Sivut eivät ole yhteisöjä vaan yksi yrityksen markkinoinnin, brändinrakennuksen ja asiakaspalvelun kanavista

Assessing the impact of physicians' social capital on decision making quality mediated by knowledge sharing in a virtual community of practice: an empirical quantitative analysis

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.Purpose - Healthcare (HC) is a globally expensive investment, suffering from service quality, due to medical errors caused by physicians’ poor decisions making (DM). Current published literature: (1) encourages clinical DM research to reduce diagnostic errors and (2) stresses on the dearth of means for practitioners’ knowledge shared DM; this research focuses on knowledge sharing for improving medical DM quality through physicians’ social capital (SC) in a virtual community of practice (VCoP). Physicians join a virtual community (VC) to share clinical practice knowledge to aid medical DM. This study aims to assess the effect of physicians’ SC on medical DM and assess the mediating role of knowledge sharing quality, between physicians’ SC and medical DM quality since research lacks to investigate the impact of knowledge management (KM) tools in a HC context. VCoP is a KM tool and medical DM quality is a HC topic of this study. Design/methodology/approach – This positivist, quantitative research utilizes non-experimental survey to empirically assess its conceptual framework. After attaining an ethical approval, from Brunel Business School Research Ethics Committee, online survey was pre-tested and pilot tested for clarity and validity. 10 non-physician Ph.D. academics voluntarily participated during the survey’s pre-test phase. The survey was amendment for its pilot study phase; conducted in “plastic surgery yahoo group” VC. 31 physician VC members voluntarily participated. Again, the survey was amended and distributed for main data collection from 204 voluntary SurveyMonkey’s VC’s physician members. Findings – Data was analysed using SPSS 20 and LISREL 8.80 by means of confirmatory factor analysis and Structural Equation Modeling. Empirical findings supported this study’s four main hypotheses as well as supported this study’s initially proposed conceptual framework. Originality/value – This study customized the Honeycomb framework to establish a definition of professional physicians; HC VCs followed by identifying 51 VCs from social networking platforms like LinkedIn, Facebook, etc. This study also fulfilled its aim and hence proposed a structurally fit conceptual framework. Keywords –Virtual Community of Practice; Healthcare Knowledge Management; Confirmatory Factor Analysis; Structural Equation Modelin

Social-Compliance in Trust Management within Virtual Communities

International audienceRecent years witnessed an ever growing impact of trust in the decision-making process within virtual communities. The inherent decentralized and open nature of such environments produced new challenges that received, up to now, little attention. For example, the individual and collective trust co-influence remains an unexplored issue. In this paper we are considering how user-centred and community-centred trust policies can be considered, managed and combined. To this aim, we propose a Socially-Compliant Trust Management Systems (SC-TMS) based on dynamic and adaptive trust policies and multi-agent technologies

Adaptiveness and social-compliance in trust management within virtual communities

International audienceThe success of virtual communities (VCs) relies on collaboration and resource sharing principles, making trust a priority for each member. The work presented in this paper addresses the problem of trust management in open and decentralised virtual communities. We address this problem by proposing an Adaptive and Socially-Compliant Trust Management System (ASC-TMS) adopting a multi-agent based approach. Our proposal relies on the joint use of trust policies and meta-policies, which allow VC members to exhibit adaptive (i.e., in accordance with environment changes) and socially-compliant (i.e., in accordance with the collective policies specified by the community members) behaviour. The experiments reported in this paper focus on the socially-compliant aspect of ASC-TMS. They aim at evaluating different policy integration algorithms