topicego

Topicego is a theoretical framework in information science and digital humanities that examines the interaction between topical content and authorial identity in online discourse and knowledge organization. It is a theoretical construct used in academic discourse to examine how topic content interacts with author identity. In practice, topicego invites analysts to study how the way a topic is framed by an author affects its reception, salience, and persistence across platforms, as well as how topics cluster around individual voices.

Core concepts include topic units, ego signals (such as author tags, user handles, and stated affiliations), audience alignment, and the tension between topic stability and personal framing. The framework emphasizes both the semantic content of messages and the social identity cues that accompany them, as well as the temporal dynamics of topic evolution.

Applications include scholarly indexing and digital archives, social media analytics, and recommender or moderation systems that weigh both topical similarity and author reputation. Methodologically, topicego can be explored with topic modeling techniques (for example, latent Dirichlet allocation or neural topic models) combined with author attribution methods and longitudinal analyses of topic trajectories. Evaluation typically considers topic coherence, attribution accuracy, and bias or fairness checks.

Critiques focus on the risk of amplifying ego-driven biases, privacy concerns, and the potential to entrench power asymmetries by privileging well-known voices. Supporters argue that the approach can improve interpretability and accountability in complex information ecosystems.

See also: topic modeling; author attribution; knowledge organization; recommender systems; discourse analysis.