Semantic Search of Memes on Twitter

• URL: http://arxiv.org/abs/2002.01462v4
• Date: Wed, 20 May 2020 23:44:26 GMT
• Title: Semantic Search of Memes on Twitter
• Authors: Jesus Perez-Martin, Benjamin Bustos, Magdalena Saldana
• Abstract summary: This paper proposes and compares several methods for automatically classifying images as memes. We experimentally evaluate the methods using a large dataset of memes collected from Twitter users in Chile.
• Score: 0.8701566919381222
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Memes are becoming a useful source of data for analyzing behavior on social media. However, a problem to tackle is how to correctly identify a meme. As the number of memes published every day on social media is huge, there is a need for automatic methods for classifying and searching in large meme datasets. This paper proposes and compares several methods for automatically classifying images as memes. Also, we propose a method that allows us to implement a system for retrieving memes from a dataset using a textual query. We experimentally evaluate the methods using a large dataset of memes collected from Twitter users in Chile, which was annotated by a group of experts. Though some of the evaluated methods are effective, there is still room for improvement.

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