Discovering similar Twitter accounts using semantics
release_uk6kz7c42bhl5f6s7caakrhjhy
by
Gerasimos Razis, Ioannis Anagnostopoulos
2015
Abstract
On daily basis, millions of Twitter accounts post a vast number of tweets
including numerous Twitter entities (mentions, replies, hashtags, photos,
URLs). Many of these entities are used in common by many accounts. The more
common entities are found in the messages of two different accounts, the more
similar, in terms of content or interest, they tend to be. Towards this
direction, we introduce a methodology for discovering and suggesting similar
Twitter accounts, based entirely on their disseminated content in terms of
Twitter entities used. The methodology is based exclusively on semantic
representation protocols and related technologies. An ontological schema is
also described towards the semantification of the Twitter accounts and their
entities.
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