Visualizing emoji usage in geo-social media across time, space, and topic
Bibliographic Data
| ID | 22092835 |
|---|---|
| Authors | Samantha Levi (Technische Universität Dresden), Eva Hauthal (0000-0001-8917-600X, Technische Universität Dresden, corresponding author), Sagnik Mukherjee (0000-0001-8938-6154, Technische Universität Dresden), Frank Ostermann (0000-0002-9317-8291, University of Twente) |
| Year | 2024 |
| Volume | 9 |
| Publication date | 2024-01-17 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Communication (JOURNAL) |
| Journal identifiers | ISSN: 2297-900X • E-ISSN: 2297-900X |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fcomm.2024.1303629 |
| OpenAlex | W4390953280 |
| Language | EN |
| Citations received | 4 |
| References cited | 33 |
Social media is ubiquitous in the modern world and its use is ever-increasing. Similarly, the use of emojis within social media posts continues to surge. Geo-social media produces massive amounts of spatial data that can provide insights into users' thoughts and reactions across time and space. This research used emojis as an alternative to text-based social media analysis in order to avoid the common obstacles of natural language processing such as spelling mistakes, grammatical errors, slang, and sarcasm. Because emojis offer a non-verbal means to express thoughts and emotions, they provide additional context in comparison to purely text-based analysis. This facilitates cross-language studies. In this study, the spatial and temporal usage of emojis were visualized in order to detect relevant topics of discussion within a Twitter dataset that is not thematically pre-filtered. The dataset consists of Twitter posts that were geotagged within Europe during the year 2020. This research leveraged cartographic visualization techniques to detect spatial-temporal changes in emoji usage and to investigate the correlation of emoji usage with significant topics. The spatial and temporal developments of these topics and their respective emojis were visualized as a series of choropleth maps and map matrices. This geovisualization technique allowed for individual emojis to be independently analyzed and for specific spatial or temporal trends to be further investigated. Emoji usage was found to be spatially and temporally heterogeneous, and trends in emoji usage were found to correlate with topics including the COVID-19 pandemic, several political movements, and leisure activities
Data science · Emoji · Geography · Geovisualization · Information visualization · Linguistics · Sarcasm · Slang · Social media · Visualization · World Wide Web · Computer Science · Digital Communication and Language · Linguistic Variation and Morphology · Sentiment Analysis and Opinion Mining · Artificial Intelligence
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| Unique citing works | 4 |
|---|---|
| Citations per year | 2 |
| Citation span | 2024 - 2026 (3) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 4 |