Non-Hierarchical Networks for Censorship-Resistant Personal Communication.

The Internet promises widespread access to the world’s collective information and fast communication among people, but common government censorship and spying undermines this potential. This censorship is facilitated by the Internet’s hierarchical structure. Most traffic flows through routers owned by a small number of ISPs, who can be secretly coerced into aiding such efforts. Traditional crypographic defenses are confusing to common users. This thesis advocates direct removal of the underlying heirarchical infrastructure instead, replacing it with non-hierarchical networks. These networks lack such chokepoints, instead requiring would-be censors to control a substantial fraction of the participating devices—an expensive proposition. We take four steps towards the development of practical non-hierarchical networks. (1) We first describe Whisper, a non-hierarchical mobile ad hoc network (MANET) architecture for personal communication among friends and family that resists censorship and surveillance. At its core are two novel techniques, an efficient routing scheme based on the predictability of human locations anda variant of onion-routing suitable for decentralized MANETs. (2) We describe the design and implementation of Shout, a MANET architecture for censorship-resistant, Twitter-like public microblogging. (3) We describe the Mason test, amethod used to detect Sybil attacks in ad hoc networks in which trusted authorities are not available. (4) We characterize and model the aggregate behavior of Twitter users to enable simulation-based study of systems like Shout. We use our characterization of the retweet graph to analyze a novel spammer detection technique for Shout.PhDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107314/1/drbild_1.pd

Complex Quantum Contagion: A Quantum-Like Approach for The Analysis of Co-Evolutionary Dynamics of Social Contagion

Modeling the dynamics of social contagion processes has recently attracted a substantial amount of interest from researchers due to its wide applicability in network science, multi-agent systems, information science, and marketing. Unlike in biological spreading, the existence of a reinforcement effect in social contagion necessitates considering the complexity of individuals in the systems. Although many studies acknowledged the heterogeneity of the individuals in their adoption of information (or behavior), there are no studies that take into account the individuals\u27 uncertainty during their decision-making despite its theoretical and experimental evidence in behavioral economics, decision science, cognitive science, or multi-agent systems. This resulted in less than optimal modeling of social contagion dynamics in the existence of phase transition in the final adoption size versus transmission probability. We believe that it is mainly because traditional approaches do not consider the uncertainty stemming from agent interactions through an information exchange that can influence individuals\u27 emotions, change subconscious feelings, and trigger subjective biases. To address this problem, we propose quantum-like generalization of social contagion analysis for the analysis of co-evolutionary dynamics of social contagion. For this purpose, we employed Inverse Born Problem (IBP) to represent probabilistic entities as complex probability amplitudes in edge-based compartmental theory and demonstrated that our novel approach performs better in the prediction of social contagion dynamics through extensive simulations on random regular networks

Information consumption on social media : efficiency, divisiveness, and trust

Over the last decade, the advent of social media has profoundly changed the way people produce and consume information online. On these platforms, users themselves play a role in selecting the sources from which they consume information, overthrowing traditional journalistic gatekeeping. Moreover, advertisers can target users with news stories using users’ personal data. This new model has many advantages: the propagation of news is faster, the number of news sources is large, and the topics covered are diverse. However, in this new model, users are often overloaded with redundant information, and they can get trapped in filter bubbles by consuming divisive and potentially false information. To tackle these concerns, in my thesis, I address the following important questions: (i) How efficient are users at selecting their information sources? We have defined three intuitive notions of users’ efficiency in social media: link, in-flow, and delay efficiency. We use these three measures to assess how good users are at selecting who to follow within the social media system in order to most efficiently acquire information. (ii) How can we break the filter bubbles that users get trapped in? Users on social media sites such as Twitter often get trapped in filter bubbles by being exposed to radical, highly partisan, or divisive information. To prevent users from getting trapped in filter bubbles, we propose an approach to inject diversity in users’ information consumption by identifying non-divisive, yet informative information. (iii) How can we design an efficient framework for fact-checking? Proliferation of false information is a major problem in social media. To counter it, social media platforms typically rely on expert fact-checkers to detect false news. However, human fact-checkers can realistically only cover a tiny fraction of all stories. So, it is important to automatically prioritizing and selecting a small number of stories for human to fact check. However, the goals for prioritizing stories for fact-checking are unclear. We identify three desired objectives to prioritize news for fact-checking. These objectives are based on the users’ perception of truthfulness of stories. Our key finding is that these three objectives are incompatible in practice.In den letzten zehn Jahren haben soziale Medien die Art und Weise, wie Menschen online Informationen generieren und konsumieren, grundlegend verändert. Auf Social Media Plattformen wählen Nutzer selbst aus, von welchen Quellen sie Informationen beziehen hebeln damit das traditionelle Modell journalistischen Gatekeepings aus. Zusätzlich können Werbetreibende Nutzerdaten dazu verwenden, um Nachrichtenartikel gezielt an Nutzer zu verbreiten. Dieses neue Modell bietet einige Vorteile: Nachrichten verbreiten sich schneller, die Zahl der Nachrichtenquellen ist größer, und es steht ein breites Spektrum an Themen zur Verfügung. Das hat allerdings zur Folge, dass Benutzer häufig mit überflüssigen Informationen überladen werden und in Filterblasen geraten können, wenn sie zu einseitige oder falsche Informationen konsumieren. Um diesen Problemen Rechnung zu tragen, gehe ich in meiner Dissertation auf die drei folgenden wichtigen Fragestellungen ein: • (i) Wie effizient sind Nutzer bei der Auswahl ihrer Informationsquellen? Dazu definieren wir drei verschiedene, intuitive Arten von Nutzereffizienz in sozialen Medien: Link-, In-Flowund Delay-Effizienz. Mithilfe dieser drei Metriken untersuchen wir, wie gut Nutzer darin sind auszuwählen, wem sie auf Social Media Plattformen folgen sollen um effizient an Informationen zu gelangen. • (ii) Wie können wir verhindern, dass Benutzer in Filterblasen geraten? Nutzer von Social Media Webseiten werden häufig Teil von Filterblasen, wenn sie radikalen, stark parteiischen oder spalterischen Informationen ausgesetzt sind. Um das zu verhindern, entwerfen wir einen Ansatz mit dem Ziel, den Informationskonsum von Nutzern zu diversifizieren, indem wir Informationen identifizieren, die nicht polarisierend und gleichzeitig informativ sind. • (iii) Wie können wir Nachrichten effizient auf faktische Korrektheit hin überprüfen? Die Verbreitung von Falschinformationen ist eines der großen Probleme sozialer Medien. Um dem entgegenzuwirken, sind Social Media Plattformen in der Regel auf fachkundige Faktenprüfer zur Identifizierung falscher Nachrichten angewiesen. Die manuelle Überprüfung von Fakten kann jedoch realistischerweise nur einen sehr kleinen Teil aller Artikel und Posts abdecken. Daher ist es wichtig, automatisch eine überschaubare Zahl von Artikeln für die manuellen Faktenkontrolle zu priorisieren. Nach welchen Zielen eine solche Priorisierung erfolgen soll, ist jedoch unklar. Aus diesem Grund identifizieren wir drei wünschenswerte Priorisierungskriterien für die Faktenkontrolle. Diese Kriterien beruhen auf der Wahrnehmung des Wahrheitsgehalts von Artikeln durch Nutzer. Unsere Schlüsselbeobachtung ist, dass diese drei Kriterien in der Praxis nicht miteinander vereinbar sind

Combating Attacks and Abuse in Large Online Communities

Internet users today are connected more widely and ubiquitously than ever before. As a result, various online communities are formed, ranging from online social networks (Facebook, Twitter), to mobile communities (Foursquare, Waze), to content/interests based networks (Wikipedia, Yelp, Quora). While users are benefiting from the ease of access to information and social interactions, there is a growing concern for users' security and privacy against various attacks such as spam, phishing, malware infection and identity theft. Combating attacks and abuse in online communities is challenging. First, today’s online communities are increasingly dependent on users and user-generated content. Securing online systems demands a deep understanding of the complex and often unpredictable human behaviors. Second, online communities can easily have millions or even billions of users, which requires the corresponding security mechanisms to be highly scalable. Finally, cybercriminals are constantly evolving to launch new types of attacks. This further demands high robustness of security defenses. In this thesis, we take concrete steps towards measuring, understanding, and defending against attacks and abuse in online communities. We begin with a series of empirical measurements to understand user behaviors in different online services and the uniquesecurity and privacy challenges that users are facing with. This effort covers a broad set of popular online services including social networks for question and answering (Quora), anonymous social networks (Whisper), and crowdsourced mobile communities (Waze). Despite the differences of specific online communities, our study provides a first look at their user activity patterns based on empirical data, and reveals the need for reliable mechanisms to curate user content, protect privacy, and defend against emerging attacks. Next, we turn our attention to attacks targeting online communities, with focus on spam campaigns. While traditional spam is mostly generated by automated software, attackers today start to introduce "human intelligence" to implement attacks. This is maliciouscrowdsourcing (or crowdturfing) where a large group of real-users are organized to carry out malicious campaigns, such as writing fake reviews or spreading rumors on social media. Using collective human efforts, attackers can easily bypass many existing defenses (e.g.,CAPTCHA). To understand the ecosystem of crowdturfing, we first use measurements to examine their detailed campaign organization, workers and revenue. Based on insights from empirical data, we develop effective machine learning classifiers to detect crowdturfingactivities. In the meantime, considering the adversarial nature of crowdturfing, we also build practical adversarial models to simulate how attackers can evade or disrupt machine learning based defenses. To aid in this effort, we next explore using user behavior models to detect a wider range of attacks. Instead of making assumptions about attacker behavior, our idea is to model normal user behaviors and capture (malicious) behaviors that are deviated from norm. In this way, we can detect previously unknown attacks. Our behavior model is based on detailed clickstream data, which are sequences of click events generated by users when using the service. We build a similarity graph where each user is a node and the edges are weightedby clickstream similarity. By partitioning this graph, we obtain "clusters" of users with similar behaviors. We then use a small set of known good users to "color" these clusters to differentiate the malicious ones. This technique has been adopted by real-world social networks (Renren and LinkedIn), and already detected unexpected attacks. Finally, we extend clickstream model to understanding more-grained behaviors of attackers (and real users), and tracking how user behavior changes over time. In summary, this thesis illustrates a data-driven approach to understanding and defending against attacks and abuse in online communities. Our measurements have revealed new insights about how attackers are evolving to bypass existing security defenses today. Inaddition, our data-driven systems provide new solutions for online services to gain a deep understanding of their users, and defend them from emerging attacks and abuse

Employees on social media: A multi-spokespeople model of CSR communication

Increasing societal and stakeholder expectations, along with easy access to information through social media, means corporations are asked for more information. The traditional approach to CSR communication, with corporations controlling what and how much to share with stakeholders has been restructured by social media, with stakeholders taking control. As legitimacy on social media is created through the positive and negative judgements of stakeholders, corporations must plan how to meet stakeholder demands for information effectively and legitimately, and this includes choosing appropriate spokespeople. Corporations in India have now turned towards their employees as CSR spokespeople. By encouraging employee activity on social media, these corporations are attempting to meet stakeholder demands and generate legitimacy through spokespeople whom stakeholders perceive as equals. This article examines that strategy and discusses its viability of using employees as spokespeople for CSR communication and engagement with stakeholder

Advances in knowledge discovery and data mining Part II

19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part II</p

News media gatekeeping on digital platforms : a strategy for enhancing brand personality and news diffusion

Abstracts in English and XhosaThis cross-sectional qualitative mixed-methods study explores how news media organisations employ their gatekeeping activities to brand their news outlets and, subsequently, how the brand helps to diffuse their news stories. The focus is primarily on how radio in Ghana has capitalised on technological advancement to create an online presence through radio online digital brand extensions, thus increasing their news outlet's availability to media audiences for enhanced news dissemination. This coincides with the burgeoning emergence of digital content creators facilitated by technological advancement in the media space, resulting in traditional media losing its position as the sole news source and agenda setter. This notwithstanding, the gatekeeping performed by traditional media outlets and their credibility built over the years was found to sustain them in the digital era. Situated within the interpretive research paradigm, this exploratory mixed-method study is approached qualitatively, with the quantitative aspect serving an auxiliary role. It is informed by the gatekeeping and signalling theories. It purposively samples six online digital news media brands made up of three radio online brand extensions, namely myjoyonline.com, peacefmonline.com and citifmonline.com, and three solely online digital news brands, namely newsghana24.com, mynewsghana.net and modernghana.com. The research design used the NodeXL software to collect quantitative data from the Twitter handles of the six online digital brands to plot 24 network visualisation graphs over one month. This is followed by semi-structured interviews with the online news editors, social media managers and social media curators of the six news organisations. The study establishes that traditional media brand extensions are greatly advantaged in the digital era compared to their solely online digital brand counterparts. The brand identities built by traditional media through their normative gatekeeping decisions has translated into large audience followings on their digital media platforms. They are observed to follow a journalistic branding orientation. Solely online digital brands on the other hand follow a marketing brand orientation and they capitalise on their digital presence to improve their finances and sustainability. The study makes a two-fold recommendation to radio online digital brands on one hand and to solely online digital media brands on the other.Ngokusebenzisa iindlela zophando ezixutyiweyo, esi sifundo siphonononga indlela amaqumrhu eendaba asebenzisa ngayo ukuhlela njengecebo lokuzakhela igama, kwaye xa selidumile elo gama liqhuba njani ekusasazeni iindaba. Kugxininiswa kwindlela amajelo osasazo ngonomathotholo eGhana abusebenzisa ngayo ubuchwepheshe ekuveleni kumaza omoya ngokwenza iminatha yonomathotholo omanyelwa kwi-intanethi, ngaloo ndlela kube kusandiswa amathuba okufumana iindaba kubaphulaphuli ngokomeleza iinkqubo zosasazo lweendaba. Oku kungqamana nokuhluma okunwenwayo kwabaqulunqi bemixholo ngobuchwepheshe bedijithali, nto leyo idala ukuba amajelo osasazo abefudula ekhona alahlekelwe yindawo yawo yesiqhelo apho ebekade ewodwa ekusasazeni iindaba nasekusekeni iajenda. Noxa kunjalo, indlela yokuhlela iindaba, esetyenziswa ngamajelo akudala nokuthembeka kwawo eluntwini okudaleke emva kweminyaka emininzi, kwenza ukuba la majelo angagqumeleleki kweli xesha lobuchwepheshe bedijithali. Esi sifundo sisebenzise amava abathathi nxaxheba nezinye iindlela ezininzi zophando kwaye sivelelwe ngenkalo yokuzathuza, lo gama inkalo yokusebenzisa amanani inendima eyidlalileyo nayo ekuncediseni uphando. Kuqwalaselwe iingcingane zokuhlela nokusasaza. Kuthathwe isampulu ngononophelo kumajelo eendaba edijithali amathandathu akhiwe ngeminatha emithathu yonomathotholo ofumaneka kwi-intanethi. La majelo ngala: myjoyonline.com, peacefmonline.com, citifmonline.com, namathathu angawomoya qha angala: newsghana24.com, mynewsghana.net, modernghana.com. Uyilo lophando lwasebenzisa isixhobo sobuchwepheshe esiyiNodeXL ekuqokeleleni iinkcukacha zolwazi ngokuqwalasela amanani, kumaqonga onxibelelwano lweTwitter kumajelo amathandathu, kwaqulunqwa iigrafu zababukeli ezingama-24 kwixesha elingangenyanga. Kwalandeliswa ngeendliwano ndlebe ezingaqingqwanga ngokupheleleyo nabahleli beendaba, abaphathi bamaqonga onxibelelwano, abagcini bamaqonga onxibelelwano amaqumrhu eendaba amathandathu amatsha. Isifundo safumanisa ukuba iminatha yosasazo yakudala inamandla kwixesha ledijithali xa ithelekiswa nale iyidijithali qwaba. Amajelo osasazo akudala selezenzele igama kwaye ukwaziwa kwamagama awo neendlela ahlela ngazo iindaba kukhokelela ekufumaneni abaphulaphuli abaninzi kumaqonga awo edijithali. Abonakala elandela icebo lokusebenzisa ukwaziwa kwegama. Amajelo edijithali qwaba wona alandela icebo lokuququzelela ukwazisa igama kwaye axhathise ngokuba nawo ekhona kumaza edijithali ukuze akhulise imali yawo nozinzo. Esi sifundo senze iingcebiso ezimacala mabini, okokuqala kumajelo oonomathotholo bedijithali, okwesibini kumajelo edijithali qwaba.Communication ScienceD. Phil. (Communication Science

Social informatics

5th International Conference, SocInfo 2013, Kyoto, Japan, November 25-27, 2013, Proceedings</p

Efecto de la comunicación en las redes sociales y el riesgo percibido en el valor de marca de destino desde la perspectiva del consumidor

El valor de marca en el contexto digital y el riesgo percibido son las piezas clave de esta tesis doctoral en la que se investiga el efecto del contenido generado por el usuario (User generated content) y el contenido generado de la empresa (Firm generated content) en el valor de marca de destinos turísticos (CBDBE – Customer based destination brand equity) y el efecto moderador del riesgo percibido en las relaciones del valor de marca. De forma específica, la tesis plantea que la comunicación en las redes sociales influye en las dimensiones del valor de marca, y éstas sobre las respuestas hacia la marca. Asimismo, se propone el efecto moderador del riesgo percibido en la relación comunicación-valor de marca, y en la relación valor de marca-respuesta del consumidor.Brand equity in the digital context and the perceived risk are the key pieces of this doctoral thesis in which the effect of the user generated content and the brand generated content is investigated in context of tourist destinations and the moderating effect of perceived risk in brand equity relationships. Specifically, the thesis states that communication in social networks influences the dimensions of brand equity. Likewise, it is proposed the moderating effect of the perceived risk on the relationship between communication on social media and brand equity