- inequality and IT
- information seeking
Eszter Hargittai is an assistant professor in the Department of Communication Studies and (by courtesy) in the Department of Sociology, and a Faculty Associate of the Institute for Policy Research at Northwestern. She moved to the Chicago area in the fall of 2003 after completing her Ph.D. in the Sociology Department at Princeton University and a post-doctoral fellowship at the Center for Arts and Cultural Policy Studies of the Woodrow Wilson School of Public and International Affairs at Princeton. She remains affiliated with the Center as a Visiting Research Collaborator. Eszter Hargittai's main research interests are the social and policy implications of information technologies. She is especially interested in how IT may contribute to or alleviate social inequalities. Much of her work has looked at differences in people's Web-use skills. In particular, she studies people's information-seeking behavior and thus has also been following the evolution of search engines and the organization and presentation of online content.
Social Implications of Information and Communication Technologies
Description: A look at the social, political, economic and cultural factors that shape ICT.
"Classifying and Coding Online Actions" by Eszter Hargittai, published by Social Science Computer Review (Jun 2004). Link to Publication
Research on how the Internet is diffusing across the population has broadened from questions about who uses the medium to what people do during their time online. With this change in focus comes a need for more detailed data on people''s online actions. In this paper, I provide a method for coding and classifying users'' online information-seeking behavior. I present an exhaustive list of ways in which a user may arrive at a Web page. The proposed methodology includes enough nuanced information to distinguish among different search actions and links. In its entirety, the coding scheme makes it possible to understand many details about the users'' sequence of actions simply by looking at the spreadsheet containing the information proposed in this paper. I also demonstrate the utility of this coding scheme with findings from a study on the online information-seeking behavior of 100 randomly selected Internet users to exemplify the utility of this coding and classification scheme.
"Do you google? Understanding search engine use beyond the hype" by Eszter Hargittai, published by First Monday (Mar 2004). Link to Publication
Much anecdotal evidence suggests that Google is the most popular search engine. However, such claims are rarely backed up by data. The reasons for this are manifold, including the difficulty in measuring search engine popularity and the multiple ways in which the concept can be understood. Here, I discuss the sources of confusion related to search engine popularity. It is problematic to make unfounded assumptions about general users’ search engine choices because by doing so we exclude a large number of people from our discussions about systems development and our understanding of how the average user finds information online.