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A text network refers to a data type that each vertex is associated with atext document and the relationship between documents is represented by edges.The proliferation of text networks such as hyperlinked webpages and academiccitation networks has led to an increasing demand for quickly developing ageneral sense of a new text network, namely text network exploration. In thispaper, we address the problem of text network exploration through constructinga heterogeneous web of topics, which allows people to investigate a textnetwork associating word level with document level. To achieve this, aprobabilistic generative model for text and links is proposed, where threedifferent relationships in the heterogeneous topic web are quantified. We alsodevelop a prototype demo system named TopicAtlas to exhibit such heterogeneoustopic web, and demonstrate how this system can facilitate the task of textnetwork exploration. Extensive qualitative analyses are included to verify theeffectiveness of this heterogeneous topic web. Besides, we validate our modelon real-life text networks, showing that it preserves good performance onobjective evaluation metrics.

Text Network Exploration via Heterogeneous Web of Topics