In this article, I want to present some findings in the field of social media mining, describing the implementation of a Word2Vec model applied to index an entire user base, providing a tool to find similarities and discover similar instances within a community.


Although many different social media platforms already offer ways to discover similar user, this set of features are mainly built for the final user, meaning that the goal is to actually display them what they want to see and not users that are actually similar to them under a business point of view.

Algorithms able to target similar users are used behind tools such as Facebook Ads, which gives the advertiser the possibility to target users that are similar to a specific set of conditions such as brands, tastes, or other demographics data.

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Social Media Embeddings Using Word2Vec: Clustering Users
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