Abstract
Social Media are sensors in the real world that can be used to measure the pulse of societies. However, the massive and unfiltered feed of messages posted in social media is a phenomenon that nowadays raises social alarms, especially when these messages contain hate speech targeted to a specific individual or group. In this context, governments and non-governmental organizations (NGOs) are concerned about the possible negative impact that these messages can have on individuals or on the society. In this paper, we present HaterNet, an intelligent system currently being used by the Spanish National Office Against Hate Crimes of the Spanish State Secretariat for Security that identifies and monitors the evolution of hate speech in Twitter. The contributions of this research are many-fold: (1) It introduces the first intelligent system that monitors and visualizes, using social network analysis techniques, hate speech in Social Media. (2) It introduces a novel public dataset on hate speech in Spanish consisting of 6000 expert-labeled tweets. (3) It compares several classification approaches based on different document representation strategies and text classification models. (4) The best approach consists of a combination of a LTSM+MLP neural network that takes as input the tweet’s word, emoji, and expression tokens’ embeddings enriched by the tf-idf, and obtains an area under the curve (AUC) of 0.828 on our dataset, outperforming previous methods presented in the literature.
Highlights
Worldwide accessibility to the Internet has incredibly reshaped our perception of the world.One of the children of the World Wide Web is Social Media (SM), which is present in many forms: online game platforms, dating apps, forums, online news services, and social networks
The classification models considered are evaluated and compared to identify the best, which is chosen to be included in HaterNet
This paper presents HaterNet, an intelligent system for the detection and analysis of hate speech in Twitter
Summary
Worldwide accessibility to the Internet has incredibly reshaped our perception of the world.One of the children of the World Wide Web is Social Media (SM), which is present in many forms: online game platforms, dating apps, forums, online news services, and social networks. Different social networks aim at different objectives: opinion transmission (Twitter or Facebook), business contacts (LinkedIn), image sharing (Instagram), video transmission (YouTube), dating (Meetic), and so on. They all have one thing in common: they aim to connect people. The power of social networking is so great that the number of worldwide users is expected to reach 3.02 billion active social media users per month by 2021. This will account for approximately one-third of the
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