Enhancing web activities with information visualization

Eduardo Graells-Garrido

Abstract: Many activities people perform on the Web are biased, including activities like reading news, searching for information and connecting with people. Sometimes these biases are inherent in social behavior (like homophily), and sometimes they are external as they affect the system (like media bias). In this thesis proposal, we describe our approach to use information visualization to enhance Web activities performed by regular people (i.e., non-experts) We understand enhancing as reducing bias effects and generating an engaging response from users. Our methodology is based on case studies. We select a Web activity, identify the biases that affect it, and evaluate how the biases affect a population from online social networks using web mining techniques, and then, we design a visualization following an interactive and playful design approach to diminish the previously identified biases. We propose to evaluate the effect of our visualization designs in user studies by comparing them with state-of-the-art techniques considering a playful experiences framework.