The Navigation of Topic Space

This poster reports on the evaluation of the topic space recommendation model, proposed here as an alternative to the personalization algorithms based on large datasets that often result in content and subject matter filter bubbles. The content filter bubbles that dominate contemporary Internet media platforms have been shown to provide users more of what they already consume and exclude relevant content at the expense of user exploration and discovery. Modern algorithms have also exhibited the problematic nature of reinforcing systematic bias.