Machine Learning

Online videos such as those streamed through YouTube are largely produced by individual users rather than traditional mass media, partly due to the incentive structure of the platforms. As part of the strategy to increase the audience, many content creators collaborate with other creators to attract subscribers and diversify their content. This behavior can be conceptualized as “coopetition” as they cooperate for their channels’ success while competing with one another for the limited pool of audience.

Neighborhoods are vaguely defined, localized regions that share similar characteristics. They are most often defined, delineated, and named by the citizens that inhabit them rather than municipal government or commercial agencies. The names of these neighborhoods play an important role as a basis for community and sociodemographic identity, geographic communication, and historical context.

In a creative process, divergent thinking needs to be stimulated to generate novel ideas; yet these ideas must be synthesized to produce something valuable. Hence to foster creativity in developing IT products, creators need to manage the tension between novelty and value. Since the forces affecting the novelty-value tension often exist outside a creator's group or organization, we apply organizational ecology theory to propose an industry-level, ecological model for understanding the novelty of IT products.

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.