Visualizing emoji usage in geo-social media across time, space, and topic

Samantha Levi, Eva Hauthal, Sagnik Mukherjee, Frank O. Ostermann
{"title":"Visualizing emoji usage in geo-social media across time, space, and topic","authors":"Samantha Levi, Eva Hauthal, Sagnik Mukherjee, Frank O. Ostermann","doi":"10.3389/fcomm.2024.1303629","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":507157,"journal":{"name":"Frontiers in Communication","volume":"111 5","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Communication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fcomm.2024.1303629","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

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.
跨时间、空间和主题的地理社交媒体中表情符号使用可视化
社交媒体在现代社会无处不在,其使用量也与日俱增。同样,表情符号在社交媒体帖子中的使用也在不断激增。地理社交媒体产生了大量的空间数据,这些数据可以让人们深入了解用户在不同时间和空间的想法和反应。本研究使用表情符号替代基于文本的社交媒体分析,以避免自然语言处理中常见的障碍,如拼写错误、语法错误、俚语和讽刺。由于表情符号提供了表达思想和情感的非语言手段,因此与纯文本分析相比,表情符号提供了额外的语境。这为跨语言研究提供了便利。在本研究中,我们对表情符号的空间和时间使用情况进行了可视化处理,以便在未经主题预过滤的 Twitter 数据集中发现相关的讨论话题。该数据集由 2020 年期间欧洲范围内带有地理标记的 Twitter 帖子组成。这项研究利用制图可视化技术来检测表情符号使用的时空变化,并研究表情符号使用与重要话题的相关性。这些主题及其相应表情符号的时空发展情况被可视化为一系列纵横图和地图矩阵。通过这种地理可视化技术,可以对单个表情符号进行独立分析,并进一步研究特定的空间或时间趋势。研究发现,表情符号的使用在空间和时间上具有异质性,表情符号的使用趋势与 COVID-19 大流行病、一些政治运动和休闲活动等主题相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信