Critical Impact of Social Networks Infodemic on Defeating Coronavirus COVID-19 Pandemic: Twitter-Based Study and Research Directions

News creation and consumption has been changing since the advent of social media. An estimated 2.95 billion people in 2019 used social media worldwide. The widespread of the Coronavirus COVID-19 resulted with a tsunami of social media. Most platforms were used to transmit relevant news, guidelines and precautions to people. According to WHO, uncontrolled conspiracy theories and propaganda are spreading faster than the COVID-19 pandemic itself, creating an infodemic and thus causing psychological panic, misleading medical advises, and economic disruption. Accordingly, discussions have been initiated with the objective of moderating all COVID-19 communications, except those initiated from trusted sources such as the WHO and authorized governmental entities. This paper presents a large-scale study based on data mined from Twitter. Extensive analysis has been performed on approximately one million COVID-19 related tweets collected over a period of two months. Furthermore, the profiles of 288,000 users were analyzed including unique users profiles, meta-data and tweets context. The study noted various interesting conclusions including the critical impact of the (1) exploitation of the COVID-19 crisis to redirect readers to irrelevant topics and (2) widespread of unauthentic medical precautions and information. Further data analysis revealed the importance of using social networks in a global pandemic crisis by relying on credible users with variety of occupations, content developers and influencers in specific fields. In this context, several insights and findings have been provided while elaborating computing and non-computing implications and research directions for potential solutions and social networks management strategies during crisis periods.Comment: 11 pages, 10 figures, Journal Articl

Health Misinformation in Search and Social Media

People increasingly rely on the Internet in order to search for and share health-related information. Indeed, searching for and sharing information about medical treatments are among the most frequent uses of online data. While this is a convenient and fast method to collect information, online sources may contain incorrect information that has the potential to cause harm, especially if people believe what they read without further research or professional medical advice. The goal of this thesis is to address the misinformation problem in two of the most commonly used online services: search engines and social media platforms. We examined how people use these platforms to search for and share health information. To achieve this, we designed controlled laboratory user studies and employed large-scale social media data analysis tools. The solutions proposed in this thesis can be used to build systems that better support people's health-related decisions. The techniques described in this thesis addressed online searching and social media sharing in the following manner. First, with respect to search engines, we aimed to determine the extent to which people can be influenced by search engine results when trying to learn about the efficacy of various medical treatments. We conducted a controlled laboratory study wherein we biased the search results towards either correct or incorrect information. We then asked participants to determine the efficacy of different medical treatments. Results showed that people were significantly influenced both positively and negatively by search results bias. More importantly, when the subjects were exposed to incorrect information, they made more incorrect decisions than when they had no interaction with the search results. Following from this work, we extended the study to gain insights into strategies people use during this decision-making process, via the think-aloud method. We found that, even with verbalization, people were strongly influenced by the search results bias. We also noted that people paid attention to what the majority states, authoritativeness, and content quality when evaluating online content. Understanding the effects of cognitive biases that can arise during online search is a complex undertaking because of the presence of unconscious biases (such as the search results ranking) that the think-aloud method fails to show. Moving to social media, we first proposed a solution to detect and track misinformation in social media. Using Zika as a case study, we developed a tool for tracking misinformation on Twitter. We collected 13 million tweets regarding the Zika outbreak and tracked rumors outlined by the World Health Organization and the Snopes fact-checking website. We incorporated health professionals, crowdsourcing, and machine learning to capture health-related rumors as well as clarification communications. In this way, we illustrated insights that the proposed tools provide into potentially harmful information on social media, allowing public health researchers and practitioners to respond with targeted and timely action. From identifying rumor-bearing tweets, we examined individuals on social media who are posting questionable health-related information, in particular those promoting cancer treatments that have been shown to be ineffective. Specifically, we studied 4,212 Twitter users who have posted about one of 139 ineffective ``treatments'' and compared them to a baseline of users generally interested in cancer. Considering features that capture user attributes, writing style, and sentiment, we built a classifier that is able to identify users prone to propagating such misinformation. This classifier achieved an accuracy of over 90%, providing a potential tool for public health officials to identify such individuals for preventive intervention

Social informatics

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

Co-creation of tourism experiences and the use of social media (ICTS) as key tools for innovation and value creation in the tourism industry

Portugal is an emerging tourism market, being worthy of attention. Besides, the tourism industry has been connected to fast changes due to the influence of social media (Web 2.0) on the lives of consumers and the shift in the economic value from products and services to the staging of experiences. This study aims to analyze the effect that several types of social media platforms (as mediators) have on the co-creation of tourism experiences (before, during and after) and the consequent satisfaction, happiness, memorability and motivation to share it online. For that effect, an online survey was developed and conducted on a sample of 410 national and international tourists. The findings showed that the use of social media has a more significant effect while planning the trip, serving as a source of inspiration for the next trip and of information about the chosen destination. Moreover, it also leads to a substantial increase in the satisfaction that tourists feel towards the trip, since the expectations are met by what they experience during the trip, which generates a greater level of happiness and memorability. This is crucial since it leads to a greater perception of value, a positive image of the destination, a bigger willingness to recommend and share the experience with followers. This makes it important for Portuguese tourism service providers and tourism department to understand how Portugal is being represented on social media pages and the reasons that motivate tourists to share their experiences online, thus influencing their followers to visit.Portugal é, atualmente, um mercado turístico emergente, sendo uma área importante a analisar. Além disso, a indústria do turismo tem estado ligada a mudanças rápidas devido à influência das redes sociais (Web 2.0) na vida dos consumidores e à mudança no valor económico, de produtos e serviços para a criação de experiências. Este estudo pretende analisar o efeito que vários tipos de redes sociais (mediadores) têm na cocriação de experiências de turismo e a consequente satisfação, felicidade, memorabilidade e motivação para as partilhar online. Assim, foi realizado um inquérito online a uma amostra de 410 turistas nacionais e internacionais. Os resultados mostraram que o uso das redes sociais tem um efeito mais significativo no planeamento da viagem, servindo como fonte de inspiração para a próxima viagem e de informação sobre o destino escolhido. Além disso, também leva a um aumento substancial na satisfação que os turistas sentem em relação à viagem, uma vez que as expectativas correspondem ao que eles vivenciam durante a viagem, o que gera um maior nível de felicidade e memorabilidade. Isto é crucial porque leva a uma maior perceção de valor, uma imagem positiva do destino, uma maior disponibilidade para recomendar e partilhar a experiência com os seguidores. Isto torna importante que os prestadores de serviços de turismo e o departamento de turismo português compreendam como Portugal está a ser representado nas redes sociais e as razões que motivam os turistas a partilhar as suas experiências online, influenciando assim os seus seguidores a visitar o destino

USER PROFILING AND PRIVACY PRESERVING FROM MULTIPLE SOCIAL NETWORKS

Ph.DDOCTOR OF PHILOSOPH

Contextual Social Networking

The thesis centers around the multi-faceted research question of how contexts may be detected and derived that can be used for new context aware Social Networking services and for improving the usefulness of existing Social Networking services, giving rise to the notion of Contextual Social Networking. In a first foundational part, we characterize the closely related fields of Contextual-, Mobile-, and Decentralized Social Networking using different methods and focusing on different detailed aspects. A second part focuses on the question of how short-term and long-term social contexts as especially interesting forms of context for Social Networking may be derived. We focus on NLP based methods for the characterization of social relations as a typical form of long-term social contexts and on Mobile Social Signal Processing methods for deriving short-term social contexts on the basis of geometry of interaction and audio. We furthermore investigate, how personal social agents may combine such social context elements on various levels of abstraction. The third part discusses new and improved context aware Social Networking service concepts. We investigate special forms of awareness services, new forms of social information retrieval, social recommender systems, context aware privacy concepts and services and platforms supporting Open Innovation and creative processes. This version of the thesis does not contain the included publications because of copyrights of the journals etc. Contact in terms of the version with all included publications: Georg Groh, [email protected] zentrale Gegenstand der vorliegenden Arbeit ist die vielschichtige Frage, wie Kontexte detektiert und abgeleitet werden können, die dazu dienen können, neuartige kontextbewusste Social Networking Dienste zu schaffen und bestehende Dienste in ihrem Nutzwert zu verbessern. Die (noch nicht abgeschlossene) erfolgreiche Umsetzung dieses Programmes führt auf ein Konzept, das man als Contextual Social Networking bezeichnen kann. In einem grundlegenden ersten Teil werden die eng zusammenhängenden Gebiete Contextual Social Networking, Mobile Social Networking und Decentralized Social Networking mit verschiedenen Methoden und unter Fokussierung auf verschiedene Detail-Aspekte näher beleuchtet und in Zusammenhang gesetzt. Ein zweiter Teil behandelt die Frage, wie soziale Kurzzeit- und Langzeit-Kontexte als für das Social Networking besonders interessante Formen von Kontext gemessen und abgeleitet werden können. Ein Fokus liegt hierbei auf NLP Methoden zur Charakterisierung sozialer Beziehungen als einer typischen Form von sozialem Langzeit-Kontext. Ein weiterer Schwerpunkt liegt auf Methoden aus dem Mobile Social Signal Processing zur Ableitung sinnvoller sozialer Kurzzeit-Kontexte auf der Basis von Interaktionsgeometrien und Audio-Daten. Es wird ferner untersucht, wie persönliche soziale Agenten Kontext-Elemente verschiedener Abstraktionsgrade miteinander kombinieren können. Der dritte Teil behandelt neuartige und verbesserte Konzepte für kontextbewusste Social Networking Dienste. Es werden spezielle Formen von Awareness Diensten, neue Formen von sozialem Information Retrieval, Konzepte für kontextbewusstes Privacy Management und Dienste und Plattformen zur Unterstützung von Open Innovation und Kreativität untersucht und vorgestellt. Diese Version der Habilitationsschrift enthält die inkludierten Publikationen zurVermeidung von Copyright-Verletzungen auf Seiten der Journals u.a. nicht. Kontakt in Bezug auf die Version mit allen inkludierten Publikationen: Georg Groh, [email protected]

Workshop Proceedings of the 12th edition of the KONVENS conference

The 2014 issue of KONVENS is even more a forum for exchange: its main topic is the interaction between Computational Linguistics and Information Science, and the synergies such interaction, cooperation and integrated views can produce. This topic at the crossroads of different research traditions which deal with natural language as a container of knowledge, and with methods to extract and manage knowledge that is linguistically represented is close to the heart of many researchers at the Institut für Informationswissenschaft und Sprachtechnologie of Universität Hildesheim: it has long been one of the institute’s research topics, and it has received even more attention over the last few years

Information of social media platforms: the case of Last.fm

Social media has become a global phenomenon. Currently, there are 2 billion active users on Facebook. However, much of the research on social media is about the consumption side of social media rather than the production or operational aspects of social media. Although research on the production side is still relatively small, it is growing, indicating that it is a fruitful area to study. This thesis attempts to contribute to this area of research to unravel the inner operations of social media with one key research question: How does social media platform organize information? The theory of digital object of Kallinikos et al. (2013) is used to investigate this question. Information display that users of a social media platform interact with is a digital object and it is constructed by two key components which are a database and algorithms. The database and the algorithms shape how information is being organized on information displays, and these influence user behaviors which are then captured as social data in the database. This thesis also critically examines the technology of recommender system by importing engineering literature on information filtering and retrieval. While newsfeed algorithm such as EdgeRank of Facebook has already been critically examined, information systems and media scholars have yet to investigate recommendation algorithms, despite the fact that they have been widely deployed all over the Internet. It is found that the key weakness of recommendation algorithms is their inability to recommend novel items. This is because the main tenet of any recommender system is to “recommend similar items to those that users already like”. Fortunately, this problem can be alleviated when recommender system is being deployed in the digital information environment of social media platforms. In turn, seven theoretical conjectures can be postulated. These are (1) navigation of information display as assembled by social media is highly interactive, (2) information organization of social media is highly unstable which would also render user behaviors unstable, (3) quality of data aggregation casts significant implications on user behaviors, (4) the amount of data captured by social media platforms limits the usefulness of their information displays, (5) output from the recommendation algorithm (recommendation list) casts real implications on user behaviors, (6) circle of friends on a social network can influence user behaviors, and (7) metadata attached to items being displayed casts influence on user behaviors. Data from Last.fm, a social media for music discovery, is used to evaluate these conjectures. The analysis supported most of the conjectures except the instability of information display and the importance of metadata attached to items being displayed. Some kinds of information organization are more stable than initially expected and some kinds of user generated contents are not so important for user behaviors