Community Informatics

Computational Archival Science (CAS) has been proposed as a trans-disciplinary field that combines computational and archival thinking. To provide grounded evidence, a foundational paper explored eight initial themes that constitute potential building blocks. In order for a CAS community to emerge, further studies are needed to test this framework. While the foundational paper for CAS provides a conceptual and theoretical basis of this new field, there is still a need to articulate useful guidelines and checkpoints that validate a CAS research agenda.

Defining neighborhood boundaries within a city is a complex and often subjective task. Neighborhoods boundaries are defined by the people that visit and live in the region, and activities that occur within those boundaries. Depending on the individual or group activity being conducted, these boundaries can change substantially. Transportation and human mobility patterns offer a novel basis on which to explore and delineate neighborhoods.

Social media has provided a huge amount of user-generated data in capturing urban dynamics. Among them, place-level human behavior has been largely detected through people’s check-in records at certain places. Conventionally, places are characterized by a set of pre-defined features, often specified by the owner of the places. In this paper, we argue that capturing socially-meaningful features and dynamics of an urban place may also be done by analyzing human activity traces.

This paper presents the findings from a project about how international students seek and acquire information during their settlement in an unknown geo-spatial environment. Through semi-structured interviews, questionnaires, and cognitive mapping with twenty international students, this study examines their information needs, information sources, and settlement experiences in the host country.