The type of media shared through social media channels has shifted from text content to include an increasingly large number of images. Visual traces resulting from people's online social behavior have the potential to reveal insights about our habits, activities and preferences. The role of social network-related factors have been well studied in previous research. Yet, few studies have sought to understand how user behavior in social networks is dependent on the image itself. The goal of my dissertation is to understand how people engage with image content, and I seek to uncover the role of presentation and image content on people's preferences. To achieve this goal, I study the image sharing communities, Flickr, Instagram and Pinterest, using quantitative and qualitative methods. First, I show how colors -- a fundamental property of an image -- could impact the virality of an image on Pinterest. I consider three dimensions of color: hue, saturation and brightness and evaluate their role in the diffusion of the image on Pinterest, while controlling for social network reach and activity. Next, I shift the focus from abstract colors to a higher-level presentation of images. I study the role of filters on the Flickr mobile application as proxies to visual computation. To understand how people use filters, I conduct an interview study with 15 Flickr mobile users about their filter use. I analyze Flickr mobile images to discover the role of filters in engaging users. Presentation is not the only factor that makes an image interesting. To gain deeper insights in what makes an image more engaging in social image sharing sites, I study the images of people on the Instagram network. I compare images of people with those that do not have faces and find that images with human faces are more engaging. I also look at the role of age and gender of people in the image in engaging users. Finally, I examine different content categories, with and without filters, and study the impact of content category on engagement. I use large-scale data from Flickr and interviews with Flickr mobile users to draw insights into filter use and content engagement. This dissertation takes a first step toward understanding content and presentation of images and how they impact one aspect of user behavior online. It provides several theoretical and design implications for effective design, creation and imposition of rules on image sharing communities. This dissertation opens up a new direction for future research in multimedia-mediated communication.

The advances in social media and social computing technologies have dramatically changed the way through which people interact, organize, and collaborate. The use of social media also makes the large-scale data revealing human behavior accessible to researchers and practitioners. The analysis and modeling of social networks formed from relatively stable online communities have been extensively studied. The research on the structural and dynamical patterns of large-scale crowds motivated by accomplishing common goals, named the cyber movement organizations (CMO) or cyber-enabled social movement organizations (CeSMO), however, is still limited to anecdotal case studies. This research is one of the first steps towards the understanding of the CMO/CeSMO based on real data collected from online social media.The focus of my research is on the study of an important type of CMO/CeSMO, the crowd-powered search behavior (also known as human flesh search, HFS), in which a large number of Web users voluntarily gathered together to find out the truth of an event or the information of a person that could not be identified by one single person or simple online searches. In this research, I have collected a comprehensive data-set of HFS. I first introduce the phenomenon of HFS and reviewed the study of online social groups/communities. Then, I present the empirical studies of both individual HFS episodes and aggregated HFS communities, and unveiled their unique topological properties. Based on the empirical findings, I propose two models to simulate evolution and topology of individual HFS networks. I conclude the dissertation with discussions of future research of CMO/CeSMO.

<p>When computational systems become increasingly mobile and ubiquitous, digital information and the use of computational systems may increasingly be immersed into the physical and social world of objects, people and practices. However, the digital, physical and social materials that make up these hybrid spaces have different characteristics and are hard to understand for users. In addition, users are themselves part in constructing and re-constructing the hybrid spaces.</p><p>The main question addressed in this thesis is whether making aspects of the digitally mediated hybrid spaces observable and accessible provides support to users. The observability may provide support for the specific task at hand or help in building an understanding for what the system does and how, an understanding that is needed to explain system output and to cope with service breakdowns. The fundament of the approach is to empower users of computational systems to actively make sense of the system themselves.</p><p>Two prototype services are described, Socifer and MobiTip. Their common denominator was to make digitally mediated parts of the hybrid spaces observable to users. Without disqualifying other kinds of information, the work focussed on digitally mediated social trails of other users.</p><p>Building on experience from the prototype work and an investigation into in seamful design, observability and awareness, I have investigated the effects of making a computational system’s social context observable to users in a way that</p><p>- is separated from the service’s main functionality in the interface, allowing it to become peripheral and non-obtrusive;</p><p>- uses simple models and little interpretation;</p><p>- to some extent opens up the service to allow for user appropriation of both service content and functionality; and</p><p>- is informative rather than proactive in order to empower the user rather than acting on the user’s behalf.</p><p>By designing systems that fulfil these criteria I claim that the user will be supported in performing the task at hand, with or without the service, and that with service use, the user will become more and more aware of the possibilities and limitations of the underlying technology. In addition, the digitally mediated hybrid spaces where physical, social and digital contexts meet constitute application domains in themselves, domains that users may enjoy exploring.</p>

When computational systems become increasingly mobile and ubiquitous, digital information and the use of computational systems may increasingly be immersed into the physical and social world of objects, people and practices. However, the digital, physical and social materials that make up these hybrid spaces have different characteristics and are hard to understand for users. In addition, users are themselves part in constructing and re-constructing the hybrid spaces. The main question addressed in this thesis is whether making aspects of the digitally mediated hybrid spaces observable and accessible provides support to users. The observability may provide support for the specific task at hand or help in building an understanding for what the system does and how, an understanding that is needed to explain system output and to cope with service breakdowns. The fundament of the approach is to empower users of computational systems to actively make sense of the system themselves. Two prototype services are described, Socifer and MobiTip. Their common denominator was to make digitally mediated parts of the hybrid spaces observable to users. Without disqualifying other kinds of information, the work focussed on digitally mediated social trails of other users. Building on experience from the prototype work and an investigation into in seamful design, observability and awareness, I have investigated the effects of making a computational system’s social context observable to users in a way that - is separated from the service’s main functionality in the interface, allowing it to become peripheral and non-obtrusive; - uses simple models and little interpretation; - to some extent opens up the service to allow for user appropriation of both service content and functionality; and - is informative rather than proactive in order to empower the user rather than acting on the user’s behalf. By designing systems that fulfil these criteria I claim that the user will be supported in performing the task at hand, with or without the service, and that with service use, the user will become more and more aware of the possibilities and limitations of the underlying technology. In addition, the digitally mediated hybrid spaces where physical, social and digital contexts meet constitute application domains in themselves, domains that users may enjoy exploring.

Consumers face several challenges using the Internet to fill health-related needs. (1) In many cases, they face a language gap as they look for information that is written in unfamiliar technical language. (2) Medical information in social media is of variable quality and may be appealing even when it is dangerous. (3) Discussion groups provide valuable social support for necessary lifestyle changes, but are variable in their levels of activity. (4) Finding less popular groups is tedious. We present solutions to these challenges. We use a novel adaptation of topic models to address the language gap. Conventional topic models discover a set of unrelated topics that together explain the combinations of words in a collection of documents. We add additional structure that provides relationships between topics corresponding to relationships between consumer and technical medical topics. This allows us to support search for technical information using informal consumer medical questions. We also analyze social media related to eating disorders. A third of these videos promote eating disorders and consumers are twice as engaged by these dangerous videos. We study the interactions of two communities in a photo-sharing site. There, a community that encourages recovery from eating disorders interacts with the pro-eating disorder community in an attempt to persuade them, but we found that this attempt entrenches the pro-eating disorder community more firmly in its position. We study the process by which consumers participate in discussion groups in an online diabetes community. We develop novel event history analysis techniques to identify the characteristics of groups in a diabetes community that are correlated with consumer activity. This analysis reveals that uniformly advertise the popular groups to all consumers impairs the diversity of the groups and limits their value to the community. To help consumers find interesting discussion groups, we develop a system for personalized recommendation for social connections. We extend matrix factorization techniques that are effective for product recommendation so that they become suitable for implicit power-law-distributed social ratings. We identify the best approaches for recommendation of a variety of social connections involving consumers, discussion groups and discussions.

Οι εφαρμογές συναίσθησης (awareness applications) αποτελούν συστήματα ενίσχυσης της αντίληψης της παρουσίας (presence) και εντάσσονται στην ευρύτερη κατηγορία των συστημάτων υποστήριξης της επικοινωνίας με τη διαμεσολάβηση υπολογιστών (computer mediated communication systems). Μια πληθώρα τέτοιων εφαρμογών – μικρών και εξειδικευμένων ακόμη – έχει αναπτυχθεί τα τελευταία χρόνια (π.χ. MSN, Facebook), ενώ αναμένεται η ευρύτερη διάδοσή τους ως αποτέλεσμα της ανάπτυξης των κινητών επικοινωνιών. Η παρούσα διπλωματική εργασία βασίζεται στην πλατφόρμα ανάπτυξης εφαρμογών συναίσθησης ASTRA. Το συγκριτικό πλεονέκτημα της πλατφόρμας απέναντι στις υπάρχουσες εφαρμογές είναι ότι είναι γενικευμένη και συνεπώς μπορεί να οδηγήσει στην ανάπτυξη πλήθους εφαρμογών με σχετικά εύκολο τρόπο, δίνοντας τεράστια ώθηση στην ευρύτερη ανάπτυξη του πεδίου. Η εργασία αποσκοπεί στην δημιουργία ενός πλαισίου αξιολόγησης (evaluation framework) εφαρμογών συναίσθησης, το οποίο θα βασίζεται κυρίως στο πρότυπο ISO 9126. Για το σκοπό αυτό θα αναλυθεί το εν λόγω πρότυπο και θα εντοπιστούν οι ιδιαίτερες διαστάσεις των συστημάτων συναίσθησης (τα οποία θα αναλυθούν ως εφαρμογές διαδικτύου). Στη συνέχεια θα ομαδοποιηθούν τα χαρακτηριστικά τους και θα ενταχθούν στα τέσσερα στοιχεία εξωτερικής ποιότητας που προβλέπει το πρότυπο. Ως πεδίο εφαρμογής του πλαισίου θα χρησιμοποιηθεί η πλατφόρμα ASTRA, η οποία θα αξιολογηθεί με βάση αυτό. Για το σκοπό της εργασίας θα αναπτυχθούν και ορισμένες εφαρμογές συναίσθησης με τη χρήση της πλατφόρμας. / This thesis presents a quality evaluation framework for awareness systems. These are Computer Mediated Communication (CMC) systems, which support people’s needs to communicate and enhance their sense of presence. In general, quality is defined by the extent to which the software meets user needs and requirements. Our framework is based on the ISO9126 standard, which includes two quality dimensions, external and internal, and defines a set of quality criteria for each. We have chosen to adopt the end-user standpoint in evaluating awareness systems, thus we model only the four criteria groups of external quality, that is, functionality, usability, reliability and efficiency. Firstly, we present a brief introduction to software quality and the ISO9126 standard. Then, we present presence and awareness systems, and discuss their emergence and the needs they serve. We continue with a broad survey of presence and awareness systems and social software. For each of the surveyed systems (the list includes Facebook, MSN, Twitter, YouTube, LinkedIn et al), we present an extensive list of features, which support user/community management and application management. A comparative table summarizes the features of the systems surveyed. Based on this discussion, we develop the proposed evaluation framework, by listing detailed criteria for each of the four groups of external quality, according to ISO9126. For each group, we list two tables of criteria, one for community management evaluation and one for application evaluation. The criteria are sub-grouped into presentation, navigation, escalation, content, applications, communication, awareness, and connectedness. Each table is followed by a brief explanation of the criteria it contains and the range of values they assume. Then we present in detail ASTRA, the first pervasive CMC system that was designed and developed in order to enhance presence without requiring users to use a computer to join. ASTRA applies a pervasive computing interface on top of a social computing system, which supports community and awareness application management. The focus-nimbus model is used to describe the awareness framework and a novel connectedness theory is validated with the system. Finally, we evaluate and classify the presence and awareness systems, including ASTRA, according to the proposed evaluation framework.

Software development has become a cognitive and collaborative knowledge-based endeavor where developers and organizations, faced with a variety of challenges and an increased demand for extensive knowledge support, push the boundaries of existing tools and work practices. Researchers and industry professionals have spent years studying collaborative work and communication media, however, the landscape of social media is rapidly changing. Thus, instead of trying to model the use of specific technologies and communication media, I seek to model the knowledge-building process itself. Doing so will not only allow us to understand specific tool and communication media use, but whole ecosystems of technologies and their impact on software development and knowledge work, revealing aspects not only unique to specific tools, but also aspects about the combination of technologies. In this dissertation, I describe the empirical studies I conducted aimed to understand social and communication media use in software development and knowledge curation within developer communities. An important part of the thesis is an additional qualitative meta-synthesis of these studies. My meta-analysis has led to a model of software development as a knowledge building process, and a theoretical framework: I describe this newly formed framework and how it is grounded in empirical work, and demonstrate how my primary studies led to its creation. My conceptualization of knowledge building withing software development and the proposed framework provide the research community with the means to pursue a deeper understanding of software development and contemporary knowledge work. I believe that this framework can serve as a basis for a theory of knowledge building in software development, shedding light on knowledge flow, knowledge productivity, and knowledge management. / Graduate

abstract: In most social networking websites, users are allowed to perform interactive activities. One of the fundamental features that these sites provide is to connecting with users of their kind. On one hand, this activity makes online connections visible and tangible; on the other hand, it enables the exploration of our connections and the expansion of our social networks easier. The aggregation of people who share common interests forms social groups, which are fundamental parts of our social lives. Social behavioral analysis at a group level is an active research area and attracts many interests from the industry. Challenges of my work mainly arise from the scale and complexity of user generated behavioral data. The multiple types of interactions, highly dynamic nature of social networking and the volatile user behavior suggest that these data are complex and big in general. Effective and efficient approaches are required to analyze and interpret such data. My work provide effective channels to help connect the like-minded and, furthermore, understand user behavior at a group level. The contributions of this dissertation are in threefold: (1) proposing novel representation of collective tagging knowledge via tag networks; (2) proposing the new information spreader identification problem in egocentric soical networks; (3) defining group profiling as a systematic approach to understanding social groups. In sum, the research proposes novel concepts and approaches for connecting the like-minded, enables the understanding of user groups, and exposes interesting research opportunities. / Dissertation/Thesis / Ph.D. Computer Science 2013

abstract: The rapid advancements of technology have greatly extended the ubiquitous nature of smartphones acting as a gateway to numerous social media applications. This brings an immense convenience to the users of these applications wishing to stay connected to other individuals through sharing their statuses, posting their opinions, experiences, suggestions, etc on online social networks (OSNs). Exploring and analyzing this data has a great potential to enable deep and fine-grained insights into the behavior, emotions, and language of individuals in a society. This proposed dissertation focuses on utilizing these online social footprints to research two main threads – 1) Analysis: to study the behavior of individuals online (content analysis) and 2) Synthesis: to build models that influence the behavior of individuals offline (incomplete action models for decision-making). A large percentage of posts shared online are in an unrestricted natural language format that is meant for human consumption. One of the demanding problems in this context is to leverage and develop approaches to automatically extract important insights from this incessant massive data pool. Efforts in this direction emphasize mining or extracting the wealth of latent information in the data from multiple OSNs independently. The first thread of this dissertation focuses on analytics to investigate the differentiated content-sharing behavior of individuals. The second thread of this dissertation attempts to build decision-making systems using social media data. The results of the proposed dissertation emphasize the importance of considering multiple data types while interpreting the content shared on OSNs. They highlight the unique ways in which the data and the extracted patterns from text-based platforms or visual-based platforms complement and contrast in terms of their content. The proposed research demonstrated that, in many ways, the results obtained by focusing on either only text or only visual elements of content shared online could lead to biased insights. On the other hand, it also shows the power of a sequential set of patterns that have some sort of precedence relationships and collaboration between humans and automated planners. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2019

<p dir="ltr">In an era where digital communication is important, Chinese English speakers face unique challenges in text-based academic settings, struggling to accurately convey emotions and tones. This study investigates the impact of AI-powered emotion analysis services (like ChatGPT with prompts) in addressing these challenges. It aims to enhance the writing and emotional expression skills of non-native English-speaking university students through AI assistance in text-based communication. Participants will engage in tasks with professors and peers as the target audience to assess the AI tool's effectiveness in adapting writing styles and improving emotional clarity. The findings highlight the potential of AI and emotion analysis services in improving email writing and emotional expression. We concluded that with the assistance of AI tools, people can perform better in email writing and emotional expression. However, there is a contradiction in the data we collected to our original hypothesis, indicating no significant differences in editing behavior with AI assistance. A discussion about ways to provide emotion analysis services is included as well. </p>