Discovering similar Twitter accounts using semantics

TL;DR

This paper presents a semantic-based methodology for discovering similar Twitter accounts by analyzing shared entities in their content, utilizing ontological schemas for semantic representation.

Contribution

It introduces a novel approach that leverages semantic protocols and ontologies to identify similar Twitter accounts based on their shared entities.

Findings

Effective in identifying similar accounts based on shared entities

Utilizes semantic representation for improved accuracy

Provides a framework for semantic analysis of Twitter content

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.