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Edward A. Fox

Publications and source records attributed to Edward A. Fox.

23 records · Page 2Linked to original sources

A Hybrid Model for Role-related User Classification on Twitter

To aid a variety of research studies, we propose TWIROLE, a hybrid model for role-related user classification on Twitter, which detects male-related, female-related, and brand-related (i.e., organization or institution) users. TWIROLE leverages features from tweet contents, user profiles, and profile images, and then applies our hybrid model to identify a user's role. To evaluate it, we used two existing large datasets about Twitter users, and conducted both intra- and inter-comparison experiments. TWIROLE outperforms existing methods and obtains more balanced results over the several roles. We also confirm that user names and profile images are good indicators for this task. Our research extends prior work that does not consider brand-related users, and is an aid to future evaluation efforts relative to investigations that rely upon self-labeled datasets.

cs.SI↗

Anatomy of Scholarly Information Behavior Patterns in the Wake of Academic Social Media Platforms

As more scholarly content is born digital or converted to a digital format, digital libraries are becoming increasingly vital to researchers seeking to leverage scholarly big data for scientific discovery. Although scholarly products are available in abundance-especially in environments created by the advent of social networking services-little is known about international scholarly information needs, information-seeking behavior, or information use. The purpose of this paper is to address these gaps via an in-depth analysis of the information needs and information-seeking behavior of researchers, both students and faculty, at two universities, one in the U.S. and the other in Qatar. Based on this analysis, the study identifies and describes new behavior patterns on the part of researchers as they engage in the information-seeking process. The analysis reveals that the use of academic social networks has notable effects on various scholarly activities. Further, this study identifies differences between students and faculty members in regard to their use of academic social networks, and it identifies differences between researchers according to discipline. Although the researchers who participated in the present study represent a range of disciplinary and cultural backgrounds, the study reports a number of similarities in terms of the researchers' scholarly activities.

cs.DL↗

Automatically Generating Interfaces for Personalized Interaction with Digital Libraries

We present an approach to automatically generate interfaces supporting personalized interaction with digital libraries; these interfaces augment the user-DL dialog by empowering the user to (optionally) supply out-of-turn information during an interaction, flatten or restructure the dialog, and enquire about dialog options. Interfaces generated using this approach for CITIDEL are described.

cs.DL↗

A Connection-Centric Survey of Recommender Systems Research

Recommender systems attempt to reduce information overload and retain customers by selecting a subset of items from a universal set based on user preferences. While research in recommender systems grew out of information retrieval and filtering, the topic has steadily advanced into a legitimate and challenging research area of its own. Recommender systems have traditionally been studied from a content-based filtering vs. collaborative design perspective. Recommendations, however, are not delivered within a vacuum, but rather cast within an informal community of users and social context. Therefore, ultimately all recommender systems make connections among people and thus should be surveyed from such a perspective. This viewpoint is under-emphasized in the recommender systems literature. We therefore take a connection-oriented viewpoint toward recommender systems research. We posit that recommendation has an inherently social element and is ultimately intended to connect people either directly as a result of explicit user modeling or indirectly through the discovery of relationships implicit in extant data. Thus, recommender systems are characterized by how they model users to bring people together: explicitly or implicitly. Finally, user modeling and the connection-centric viewpoint raise broadening and social issues--such as evaluation, targeting, and privacy and trust--which we also briefly address.

cs.IR↗

Use and usability in a digital library search system

Digital libraries must reach out to users from all walks of life, serving information needs at all levels. To do this, they must attain high standards of usability over an extremely broad audience. This paper details the evolution of one important digital library component as it has grown in functionality and usefulness over several years of use by a live, unrestricted community. Central to its evolution have been user studies, analysis of use patterns, and formative usability evaluation. We extrapolate that all three components are necessary in the production of successful digital library systems.

cs.DL↗