Research on newcomer roles in peer production sites (e.g., Wikipedia) is characterized by a broad and relatively well articulated set of functionally and culturally recognizable roles. But not all communities come with well-defined roles that newcomers can aspire to occupy. The present study explores activity clusters newcomers create when faced with few recognizable roles to fill and limited access to other participants' work that serves as an exemplar. Drawing on a mixed method research design, we present findings from an analysis of 1,687 newcomers' sessions in an online citizen science project. Our analysis revealed three major findings: (1) newcomers' activities exists across six session types; (2) newcomers toggle between light work sessions and more involved types of production or community engagement; (3) high-level contributors contribute large volumes of work but comment very little and another group contributes large volumes of comments, but works very little. The former group draws heavily on posts contributed by the latter group. Identifying shifts and regularities in contribution facilitate improved mechanisms for engaging participants and for the design of online citizen science communities.

A new ontological-content-based method for ranking the relevancy of items in the electronic newspapers domain is proposed. The method is being implemented in ePaper, a personalized electronic newspaper research project. The content-based part of the filtering method of ePaper utilizes a hierarchical ontology of news items. The method considers common and "close" ontology concepts appearing in the user's profile and in the item's profile, measuring the hierarchical distance between concepts in the two profiles. Based on the number of common and related concepts, and their distances from each other, the filtering algorithm computes the similarity between items and users, and rank-orders the news items according to their relevancy to each user, thus providing a personalized newspaper.