Abstract
Social media platforms such as Twitter are extensively used for expressing and exchanging thoughts, opinions, ideas, and feelings, i.e., reactions concerning a topic or an event. Factual information about an event to which people are reacting can be obtained from different types of (geo-)sensors, official authorities, or the public press. However, these sources hardly reveal the emotional or attitudinal impact of events on people, which is, for example, reflected in their reactions on social media. Two approaches that utilize emojis are proposed to obtain the sentiment and emotions contained in social media reactions. Subsequently, these two approaches, along with visualizations that focus on space, time, and topic, are applied to Twitter reactions in the example case of Brexit.
Highlights
Social media platforms offer users the opportunity to inform themselves about topics and events and to express and exchange thoughts, opinions, ideas, and feelings publicly or within a particular group of people
For instance, a tweet, addresses a specific event, this tweet can be regarded as a reaction to the event
Hashtags and emojis classified as positive or negative are combined to determine the sentiment of a reaction; on the other hand, emojis assigned to emotional categories are used as indicators of joy, fear, sadness, and other emotions within a reaction
Summary
Social media platforms offer users the opportunity to inform themselves about topics and events and to express and exchange thoughts, opinions, ideas, and feelings publicly or within a particular group of people. Hashtags and emojis classified as positive or negative are combined to determine the sentiment of a reaction; on the other hand, emojis assigned to emotional categories are used as indicators of joy, fear, sadness, and other emotions within a reaction Both approaches are applied to and discussed for the example case of Brexit, i.e., the withdrawal of the United Kingdom (UK) from the European Union (EU). This investigation of emotional reactions in LBSM to Brexit, which is regarded from different perspectives by focusing on space, time, or topic of the reactions to describe, visualize, and analyze them, shows which kinds of insight emoji-filled social media data can give. This paper presents a case study to review the validity of this approach
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