TiDeH: Time-Dependent Hawkes Process for Predicting Retweet Dynamics

Online social networking services allow their users to post content in the form of text, images or videos. The main mechanism driving content diffusion is the possibility for users to re-share the content posted by their social connections, which may then cascade across the system. A fundamental problem when studying information cascades is the possibility to develop sound mathematical models, whose parameters can be calibrated on empirical data, in order to predict the future course of a cascade after a window of observation. In this paper, we focus on Twitter and, in particular, on the temporal patterns of retweet activity for an original tweet. We model the system by Time-Dependent Hawkes process (TiDeH), which properly takes into account the circadian nature of the users and the aging of information. The input of the prediction model are observed retweet times and structural information about the underlying social network. We develop a procedure for parameter optimization and for predicting the future profiles of retweet activity at different time resolutions. We validate our methodology on a large corpus of Twitter data and demonstrate its systematic improvement over existing approaches in all the time regimes.Comment: The manuscript has been accepted in the 10th International AAAI Conference on Web and Social Media (ICWSM 2016

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

FINDING HER MASTER’S VOICE: THE POWER OF COLLECTIVE ACTION AMONG FEMALE MUSLIM BLOGGERS

Emerging cyber-collective movements have frequently made headlines in the news. Despite the exponential growth of bloggers in Muslim countries, there is a lack of empirical study of cyber-collective actions in these countries. We analyzed the female Muslim blogosphere because very little research attempts to understand socio-political roles of female bloggers in the system where women are frequently denied freedom of expression. We collected 150 blogs from 17 countries ranging between April 2003 and July 2010 with a special focus on Al-Huwaider’s campaigns for our analysis. Bearing the analysis upon three central tenets of individual, community, and transnational perspectives, we develop novel algorithms modeling cyber-collective movements by utilizing existing social theories on collective action and computational social network analysis. This paper contributes a methodology to study the diffusion of issues in social networks and examines roles of influential community members. We also observe the transcending nature of cyber-collective movements with future possibilities for modeling transnational outreach. Using the global female Muslim blogosphere, we provide understanding of the complexity and dynamics of cyber-collective action. To the best of our knowledge, our research is the first to address the lacking fundamental research shedding light on re-framing collective action theory in online environments

A survey on cost-effective context-aware distribution of social data streams over energy-efficient data centres

Social media have emerged in the last decade as a viable and ubiquitous means of communication. The ease of user content generation within these platforms, e.g. check-in information, multimedia data, etc., along with the proliferation of Global Positioning System (GPS)-enabled, always-connected capture devices lead to data streams of unprecedented amount and a radical change in information sharing. Social data streams raise a variety of practical challenges, including derivation of real-time meaningful insights from effectively gathered social information, as well as a paradigm shift for content distribution with the leverage of contextual data associated with user preferences, geographical characteristics and devices in general. In this article we present a comprehensive survey that outlines the state-of-the-art situation and organizes challenges concerning social media streams and the infrastructure of the data centres supporting the efficient access to data streams in terms of content distribution, data diffusion, data replication, energy efficiency and network infrastructure. We systematize the existing literature and proceed to identify and analyse the main research points and industrial efforts in the area as far as modelling, simulation and performance evaluation are concerned

Popularity-based video caching techniques for cache-enabled networks: a survey

The proliferation of the mobile Internet and connected devices, which offer a variety of services at different levels of performance is a major challenge for the fifth generation of wireless networks and beyond. Innovative solutions are needed to leverage recent advances in machine storage/memory, context awareness, and edge computing. Cache-enabled networks and techniques such as edge caching are envisioned to reduce content delivery times and traffic congestion in wireless networks. Only a few contents are popular, accounting for the majority of viewers, so caching them reduces the latency and download time. However, given the dynamic nature of user behavior, the integration of popularity prediction into caching is of paramount importance to better network utilization and user satisfaction. In this paper, we first present an overview of caching in wireless networks and then provide a detailed comparison of traditional and popularity-based caching. We discuss the attributes of videos and the evaluation criteria of caching policies. We summarize some of the recent work on proactive caching, focusing on prediction strategies. Finally, we provide insight into the potential opportunities and challenges as well as some open research problems enable the realization of efficient deployment of popularity-based caching as part of the next-generation mobile networks

The Web of False Information: Rumors, Fake News, Hoaxes, Clickbait, and Various Other Shenanigans

A new era of Information Warfare has arrived. Various actors, including state-sponsored ones, are weaponizing information on Online Social Networks to run false information campaigns with targeted manipulation of public opinion on specific topics. These false information campaigns can have dire consequences to the public: mutating their opinions and actions, especially with respect to critical world events like major elections. Evidently, the problem of false information on the Web is a crucial one, and needs increased public awareness, as well as immediate attention from law enforcement agencies, public institutions, and in particular, the research community. In this paper, we make a step in this direction by providing a typology of the Web's false information ecosystem, comprising various types of false information, actors, and their motives. We report a comprehensive overview of existing research on the false information ecosystem by identifying several lines of work: 1) how the public perceives false information; 2) understanding the propagation of false information; 3) detecting and containing false information on the Web; and 4) false information on the political stage. In this work, we pay particular attention to political false information as: 1) it can have dire consequences to the community (e.g., when election results are mutated) and 2) previous work show that this type of false information propagates faster and further when compared to other types of false information. Finally, for each of these lines of work, we report several future research directions that can help us better understand and mitigate the emerging problem of false information dissemination on the Web

Raising and Rising Voices in Social Media - A Novel Methodological Approach in Studying Cyber-Collective Movements

Emerging cyber-collective social movements (CSMs) have frequently made headlines in the news. Despite their popularity, there is a lack of systematic methodologies to empirically study such movements in complex online environments. Using the Al-Huwaider online campaign as a case to illustrate our methodology, this contribution attempts to establish a rigorous and fundamental analysis that explains CSMs. We collected 150 blogs from 17 countries ranging between April 2003 and July 2010 with a special focus on Al-Huwaider’s campaigns capturing multi-cultural aspects for our analysis. Bearing the analysis upon three central tenets of individual, community, and transnational perspectives, we develop novel algorithms modeling CSMs by utilizing existing collective action theories and computational social network analysis. This article contributes a methodology to study the diffusion of issues in social networks and examines roles of influential community members. The proposed methodology provides a rigorous tool to understand the complexity and dynamics of CSMs. Such methodology also assists us in observing the transcending nature of CSMs with future possibilities for modeling transnational outreach. Our study addresses the lack of fundamental research on the formation of CSMs. This research contributes novel methodologies that can be applied to many settings including business, marketing and many others, beyond the exemplary setting chosen here for illustrative purposes