Wikis have been found to be an easy-to-use, low-cost, and Internet-based technology useful in creating and mobilizing knowledge. Wikis hosted within firms (corporate wikis) have become a popular way for employees to share information and collaborate. Preliminary research suggested that as few as 6% of wiki consumers contributed to the development of wiki pages. Conventional approaches argued that employees judged the costs of participating in wikis (e.g., authoring or changing material, reading messages, following an argument, and posting responses) to exceed the benefits of participating in wikis (e.g., recognition, reputation etc.) - thus many people "lurked" but did not post. Considering that people contemplated perceived benefits with costs of participating in wikis, research emphasized the cognitive aspects of decision-making. The emotional aspects of wiki participation in firms have received little research attention. Yet, research in other fields such as law, economics, and health showed that emotions played a critical role in human decision making, where feelings were shown to outweigh contemplated costs and benefits. For example, Kiviniemi, Voss-Humke, and Siefert (2007) found that positive feelings about exercise resulted in more physical activity whereas positive feelings about food resulted in unhealthy food choices. For Wikipedia, a public wiki, studies suggested that emotion might be an important motivator in participation. The purpose of this research was to study the role of emotion in corporate wiki participation. Since the area of research is new, the contextual details of wikis in an organizational setting made it difficult for a researcher to separate the context from the main effects. A grounded theory approach was needed. Under grounded theory, one starts with the data and builds arguments or theories from the "ground up." This study used a grounded theory methodology to reveal data through interviews, employee journals, observations, wiki statistics, and other documentation. Data were analyzed on a continuum using grounded theory coding to identify codes, categories, concepts, and properties and to recognize relationships among concepts. An exploration of emotion in an organizational context resulted in theories that provided an important beginning to understanding wiki experiences and improving wiki outcomes.

<p>This thesis is concerned with the design, development, and evaluation of information visualization tools for supporting exploratory browsing. Information retrieval (IR) systems currently do not support browsing well. Responding to user queries, IR systems typically compute relevance scores of documents and then present the document surrogates to users in order of relevance. Other systems such as email clients and discussion forums simply arrange messages in reverse chronological order. Using these systems, people cannot gain an overview of a collection easily, nor do they receive adequate support for finding potentially useful items in the collection.</p> <p>This thesis explores the feasibility of using social interaction history to improve exploratory browsing. Social interaction history refers to traces of interaction among users in an information space, such as discussions that happen in the blogosphere or online newspapers through the commenting facility. The basic hypothesis of this work is that social interaction history can serve as a good indicator of the potential value of information items. Therefore, visualization of social interaction history would offer navigational cues for finding potentially valuable information items in a collection.</p> <p>To test this basic hypothesis, I conducted three studies. First, I ran statistical analysis of a social media data set. The results showed that there were positive relationships between traces of social interaction and the degree of interestingness of web articles. Second, I conducted a feasibility study to collect initial feedback about the potential of social interaction history to support information exploration. Comments from the participants were in line with the research hypothesis. Finally, I conducted a summative evaluation to measure how well visualization of social interaction history can improve exploratory browsing. The results showed that visualization of social interaction history was able to help users find interesting articles, to reduce wasted effort, and to increase user satisfaction with the visualization tool.</p>

<p>This thesis is concerned with the design, development, and evaluation of information visualization tools for supporting exploratory browsing. Information retrieval (IR) systems currently do not support browsing well. Responding to user queries, IR systems typically compute relevance scores of documents and then present the document surrogates to users in order of relevance. Other systems such as email clients and discussion forums simply arrange messages in reverse chronological order. Using these systems, people cannot gain an overview of a collection easily, nor do they receive adequate support for finding potentially useful items in the collection.</p> <p>This thesis explores the feasibility of using social interaction history to improve exploratory browsing. Social interaction history refers to traces of interaction among users in an information space, such as discussions that happen in the blogosphere or online newspapers through the commenting facility. The basic hypothesis of this work is that social interaction history can serve as a good indicator of the potential value of information items. Therefore, visualization of social interaction history would offer navigational cues for finding potentially valuable information items in a collection.</p> <p>To test this basic hypothesis, I conducted three studies. First, I ran statistical analysis of a social media data set. The results showed that there were positive relationships between traces of social interaction and the degree of interestingness of web articles. Second, I conducted a feasibility study to collect initial feedback about the potential of social interaction history to support information exploration. Comments from the participants were in line with the research hypothesis. Finally, I conducted a summative evaluation to measure how well visualization of social interaction history can improve exploratory browsing. The results showed that visualization of social interaction history was able to help users find interesting articles, to reduce wasted effort, and to increase user satisfaction with the visualization tool.</p>

Due to online social media, access to information is becoming easier and easier. Meanwhile, the truthfulness of online information is often not guaranteed. Incorrect information, often called misinformation, can have several modalities, and it can spread to multiple social media platforms in different languages, which can be destructive to society. However, academia and industry do not have automated ways to assess the impact of misinformation on social media, preventing the adoption of productive strategies to curb the prevalence of misinformation. In this dissertation, I present my research to build computational pipelines that help measuring and detecting misinformation on social media. My work can be divided into three parts. The first part focuses on processing misinformation in text form. I first show how to group political news articles from both trustworthy and untrustworthy news outlets into stories. Then I present a measurement analysis on the spread of stories to characterize how mainstream and fringe Web communities influence each other. The second part is related to analyzing image-based misinformation. It can be further divided into two parts: fauxtography and generic image misinformation. Fauxtography is a special type of image misinformation, where images are manipulated or used out-of-context. In this research, I present how to identify fauxtography on social media by using a fact-checking website (Snopes.com), and I also develop a computational pipeline to facilitate the measurement of these images at scale. I next focus on generic misinformation images related to COVID-19. During the pandemic, text misinformation has been studied in many aspects. However, very little research has covered image misinformation during the COVID-19 pandemic. In this research, I develop a technique to cluster visually similar images together, facilitating manual annotation, to make subsequent analysis possible. The last part is about the detection of misinformation in text form following a multi-language perspective. This research aims to detect textual COVID-19 related misinformation and what stances Twitter users have towards such misinformation in both English and Chinese. To achieve this goal, I experiment on several natural language processing (NLP) models to investigate their performance on misinformation detection and stance detection in both monolingual and multi-lingual manners. The results show that two models: COVID-Tweet-BERT v2 and BERTweet are generally effective in detecting misinformation and stance in the two above manners. These two models are promising to be applied to misinformation moderation on social media platforms, which heavily depends on identifying misinformation and stance of the author towards this piece of misinformation. Overall, the results of this dissertation shed light on understanding of online misinformation, and my proposed computational tools are applicable to moderation of social media, potentially benefitting for a more wholesome online ecosystem.

Aktivitetsteorin har rötterna i psykologin men har på senare år använts inom många andra områden, bland annat inom informationsteknologi. Teorin innehåller sex aktörer som används för att identifiera olika delar av ett system för att sedan se hur de påverkar varandra och systemet. Användning av aktivitetsteorin gör att fokus förflyttas från själva teknologin som används till att se teknologin ur ett socialt och kulturellt perspektiv. Teorin är väl utforskad teoretiskt, men mindre utforskad i praktiken. För att utforska möjligheterna med aktivitetsteorin kombinerades den i detta arbete med ämnet psykisk ohälsa. Psykisk ohälsa är ett samhällsproblem som har blivit mer uppmärksammat på senare år, men situationen förbättras inte. Utöver den sjukvård som finns tillgänglig idag för att behandla psykisk ohälsa finns även stödlinjer för att ge stöd åt personer med psykisk ohälsa. I detta kandidatarbete gjordes en fallstudie med den ideella verksamheten Mind som arbetar med att främja psykiskt välbefinnande. De har en stödlinje som heter Självmordslinjen där volontärer samtalar genom chatt eller telefonsamtal med personer som söker stöd i sitt psykiska mående. För att undersöka aktivitetsteorins möjligheter i detta sammanhang utfördes enanalys av kommunikationen som sker mellan volontärerna och stödsökande utifrån volontärernas perspektiv. Studiens datainsamling inleddes med en informationsinsamling om verksamheten. Efter detta hölls en enkät för volontärerna att svara på följt av fyra intervjuer. Insamlade data analyserades sedan med hjälp av aktivitetsteorin. Detta resulterade i insikter om vilka aktörer som ingår i kommunikationen samt hur de påverkar varandra i helhet. Aktivitetsteorin visade sig ge en god översikt över stödlinjen, men vissa svagheter hittades också med teorin i just detta sammanhang, såsom att teorin endast kan anta ett perspektiv. / The activity theory has its roots in psychology but has lately been used in many other fields, such as information technology. The theory includes six actors that are used to identify different parts of a system to then see how they affect each other and the system. The use of the activity theory shifts the focus from the technology that is used to seeing the technology from a social and cultural perspective. The theory is well explored in theory, but less explored in practice. To explore the possibilities with the activity theory it was in this bachelor’s thesis combined with the subject of mental health issues. Mental health is a societal problem that has gotten more attention in the past few years, but the situation is not improving. Beyond the healthcare available today to treat mental health issues there are also helplines to provide support for people with mental health issues. In this bachelor’s thesis, a case study was performed with the non-profit organization Mind which works to promote mental wellbeing. They have a helpline called Självmordslinjen where volunteers speak through the phone or via chat with people seeking support for their mental health. To examine the possibilities of the activity theory in this context, an analysis was performed on the communication between the volunteers and the people in need of support from the volunteers’ perspective. The data collection of the study was initiated with a collection of information about the organization. After this, a questionnaire was held for the volunteers to answer followed by four interviews. The collected data were then analyzed using the activity theory. This resulted in insights into which actors are involved in the communication and how they affect eachother as a whole. The activity theory gave a good overview of the helpline, but some weaknesses were also found in the theory in this context, like the fact that the theory can only adopt one perspective.

Ample research has been conducted to identify the determinants of information technology (IT) adoption. No previous quantitative researchers have explored IT adoption in the context of enterprise social computing (ESC). The purpose of this study was to test and extend the social influence model of IT adoption. In addition, this study addressed a gap in the research literature and presented a model that relates the independent variables of social action, social consensus, social authority, social cooperation, perceived relative advantage, perceived compatibility, perceived ease of use, perceived usefulness, and organizational commitment to the dependent variables of social embracement and embedment. A randomized stepwise multiple linear regression analysis was performed on survey data from 125 C-level executives (i.e., chief information officers and chief technology officers). The analysis found that executives consider perceived relative advantage, organizational commitment, and social computing action as the most significant factors relating to the adoption of ESC. Executives' perceptions about ESC could impact organizational commitment, implementation, and use of such technologies. The findings could make a social contribution within organizations by helping C-level executives understand the degree to which these factors contribute to the ESC adoption. The knowledge from this study may also help organizations derive operational effectiveness, efficiency, and create business value for their clients and society.

Since the late twentieth century, open source software projects (e.g., the GNU/Linux operating system, the Apache web server, Perl and many others) have achieved phenomenal success. This success can be attributed to a new paradigm of productivity in which individuals voluntarily collaborate to produce knowledge, goods and services. Benkler claims this productivity paradigm is a “new, third mode of production” particularly suited for “the digitally networked environment” (2002). In addition to its application to open source software projects, the peer production model, in different forms, has been used in areas such as science/citizen science (Silvertown, 2009), library science (Weinberger, 2007), politics (Castells, 2007; Jenkins, 2006), education (Daniel, 2012), journalism (Gillmor, 2004), and culture (Jenkins, 2006; Lessig, 2004). As peer production has flourished, merely describing successful cases has become less useful. Instead, scholars must identify the dynamics, structures, and conditions that contribute to or impede that success. In this dissertation, I focus on three management challenges at three distinct levels that impede the success of peer production. At the individual level, one significant question is how to best organize individual contributors with differing goals, experience, and commitment to achieve a collective outcome. At the practice level, peer production communities, like corporations, must often transfer best practices from one unit to another to improve performance. This transfer process poses the challenge of how to adapt and modify an original practice to make it effective in the new context. At the community level, peer production communities must learn to survive and succeed in a large ecosystem of related communities. This dissertation combines theoretical approaches in organization science with in-depth empirical analysis on a range of peer production communities to examine the mechanisms that help the communities overcome these three management challenges and succeed in peer production. The contributions of my dissertation are twofold. For scholars and researchers, my dissertation advances the theoretical understanding of the underlying mechanisms of successful peer production systems. For practitioners, my dissertation offers practical advice to build more effective peer production projects and platforms.

Online networks of individuals have been used to solve a number of problems in a scale that would not be possible if not within a connected, virtual and social environment such as the internet. However, the quality of solutions provided by individuals of an online network can vary significantly thus making work quality unreliable. This dissertation investigates factors that can influence the quality of the work output of individuals in online social networks. Specifically, we show that when solving tasks with small duration (under 5 minutes), also known as microtasks, individuals decision making will be strongly biased by costs of searching (and evaluating) options rather than financial or non-financial incentives. Indeed, we are able to show that we can influence individuals decisions, when solving problems, by rearranging elements visually to modify an the search sequence of an individual, be it by designing the virtual work environment or manipulating which options are first shown in non-controlled environments such as the Amazon Mechanical Turk labor market. We performed several experiments in online networks where individuals are invited to work on tasks with varying degrees of difficulty within three settings: mathematical games with objective truth (Sudoku and SAT instances), surveys with subjective evaluation (public policy polling) and labor markets (Amazon Mechanical Turk). We show that the time spent solving problems and the user interface are more relevant to the quality of work output than previous research have assumed and that individuals do not change this behavior while solving the sets of problems. Finally, to complement our study of online problem-solving, we present additional experiments in an online labor market (Amazon Mechanical Turk) that agrees with our networked experiments, shedding new light on how and why people solve problems.

Metódos analíticos de investigação são usualmente ineficazes para sistemas computacionais sociais já que apenas algumas iterações do sistema já são suficientes para que o sistema se torne imprevisível. Portanto, uma das principais questões na Computação Social é o desenvolvimento de modelos sociais passíveis de investigação. Assim é possível que se compreenda o relacionamento complexo entre os componentes de sistemas sociais computacionais e o resultado. Este aspectos incluem a modelagem, a estrutura de comunicação e características individuais do agentes envolvidos na resolução dos problemas. do processo social. Esta tese explora sistemas computacionais de resolução de problemas com foco em sistemas artificiais e heterogêneos. Nela é feita uma compilação extensiva da literatura relacionada em sistemas complexos onde as contribuições do candidato são expostas dentro de contextos específicos da área. Entre elas está o estudo de modelos abstratos e gerais de resolução social de problemas, a investigação do impacto da centralidade no resultado individual e coletivo, a análise experimental de modelos heterogêneos de resolução social de problemas. Quando integradas, estas contribuições reforçam o entendimento sobre a importância da rede e das estruturas de comunicação, a composição estratégica do sistema, a estrutura do problema e possíveis padrões gerais na resolução social de problemas. / This thesis reviews and investigates social problem-solving with a particular focus on artificial and heterogeneous systems. More specifically, we not only compile and comprehensively examine recent research results, but also discuss future directions in the study of such heterogeneous complex systems. Given their complex nature, such systems often defy analyses. Even computationally simple models can behave unpredictably after a few iterations. Therefore, one central issue in Social Computing is to devise models of social interaction that are amenable to investigation. This way, one can understand the complex relationships among the components and the outcome of the social process. This thesis surveys scientific inquiries concerned with fundamental aspects in social problemsolving systems and their impact in ability and performance of such systems. These aspects include modeling, communication structure and individual problem-solver traits. This thesis also reports the student endeavour during the period of research and summarizes several already published contributions. Among them there is (i) the study of general frameworks for the study of social problem-solving, (ii) the investigation of the role of centrality in individual and collective outcomes, and (iii) the exploration of heterogeneous models of social problem-solving. These three points, in an integrated perspective underpin the understanding of network and communication structures, adjust the strategic systems’ composition, and exploit problems’ structures and patterns in social problemsolving systems.

Sistemas sociais têm se tornado cada vez mais relevantes para a Ciência da Computação em geral e para a Inteligência Artificial em particular. Tal interesse iniciou-se pela necessidade de analisar-se sistemas baseados em agentes onde a interação social destes agentes pode ter um impacto no resultado esperado. Uma tendência mais recente vem da área de Processamento Social de Informações, Computação Social e outros métodos crowdsourced, que são caracterizados por sistemas de computação compostos de pessoas reais, com um forte componente social na interação entre estas. O conjunto de todas interações sociais e os atores envolvidos compõem uma rede social, que pode ter uma forte influência em o quão eficaz ou eficiente o sistema pode ser. Nesta tese, exploramos o papel de estruturas de redes em sistemas sociais que visam a solução de problemas. Enquadramos a solução de problemas como uma busca por soluções válidas em um espaço de estados e propomos um modelo - a Rede Memética - que é capaz de realizar busca utilizando troca de informações (memes) entre atores interagindo em uma rede social. Tal modelo é aplicado a uma variedade de cenários e mostramos como a presença da rede social pode melhorar a capacidade do sistema em encontrar soluções. Adicionalmente, relacionamos propriedades específicas de diversas redes bem conhecidas ao comportamento observado para os algoritmos propostos, resultando em um conjunto de regras gerais que podem melhorar o desempenho de tais sistemas sociais. Por fim, mostramos que os algoritmos propostos são competitivos com técnicas tradicionais de busca heurística em diversos cenários. / Social systems are increasingly relevant to computer science in general and artificial intelligence in particular. Such interest was first sparkled by agent-based systems where the social interaction of such agents can be relevant to the outcome produced. A more recent trend comes from the general area of Social Information Processing, Social Computing and other crowdsourced systems, which are characterized by computing systems composed of people and strong social interactions between them. The set of all social interactions and actors compose a social network, which may have strong influence on how effective the system can be. In this thesis, we explore the role of network structure in social systems aiming at solving problems, focusing on numerical and combinatorial optimization. We frame problem solving as a search for valid solutions in a state space and propose a model - the Memetic Network - that is able to perform search by using the exchange of information, named memes, between actors interacting in a social network. Such model is applied to a variety of scenarios and we show that the presence of a social network greatly improves the system capacity to find good solutions. In addition, we relate specific properties of many well-known networks to the behavior displayed by the proposed algorithms, resulting in a set of general rules that may improve the performance of such social systems. Finally, we show that the proposed algorithms can be competitive with traditional heuristic search algorithms in a number of scenarios.