Relations between Reputation and Social Media Marketing Communication in Cryptocurrency Markets: Visual Analytics using Tableau

Sejung Park, H. Park
{"title":"Relations between Reputation and Social Media Marketing Communication in Cryptocurrency Markets: Visual Analytics using Tableau","authors":"Sejung Park, H. Park","doi":"10.5392/IJOC.2021.17.1.001","DOIUrl":null,"url":null,"abstract":"Visual analytics is an emerging research field that combines the strength of electronic data processing and human intuition-based social background knowledge. This study demonstrates useful visual analytics with Tableau in conjunction with semantic network analysis using examples of sentiment flow and strategic communication strategies via Twitter in a blockchain domain. We comparatively investigated the sentiment flow over time and language usage patterns between companies with a good reputation and firms with a poor reputation. In addition, this study explored the relations between reputation and marketing communication strategies. We found that cryptocurrency firms more actively produced information when there was an increased public demand and increased transactions and when the coins’ prices were high. Emotional language strategies on social media did not affect cryptocurrencies’ reputations. The pattern in semantic representations of keywords was similar between companies with a good reputation and firms with a poor reputation. However, the reputable firms communicated on a wide range of topics and used more culturally focused strategies, and took more advantages of social media marketing by expanding their outreach to other social media networks. The visual big data analytics provides insights into business intelligence that helps informed policies.","PeriodicalId":31343,"journal":{"name":"International Journal of Contents","volume":"17 1","pages":"1-10"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Contents","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5392/IJOC.2021.17.1.001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Visual analytics is an emerging research field that combines the strength of electronic data processing and human intuition-based social background knowledge. This study demonstrates useful visual analytics with Tableau in conjunction with semantic network analysis using examples of sentiment flow and strategic communication strategies via Twitter in a blockchain domain. We comparatively investigated the sentiment flow over time and language usage patterns between companies with a good reputation and firms with a poor reputation. In addition, this study explored the relations between reputation and marketing communication strategies. We found that cryptocurrency firms more actively produced information when there was an increased public demand and increased transactions and when the coins’ prices were high. Emotional language strategies on social media did not affect cryptocurrencies’ reputations. The pattern in semantic representations of keywords was similar between companies with a good reputation and firms with a poor reputation. However, the reputable firms communicated on a wide range of topics and used more culturally focused strategies, and took more advantages of social media marketing by expanding their outreach to other social media networks. The visual big data analytics provides insights into business intelligence that helps informed policies.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
加密货币市场中声誉与社交媒体营销传播之间的关系:使用Tableau进行可视化分析
视觉分析是一个新兴的研究领域,它结合了电子数据处理的优势和基于人类直觉的社会背景知识。本研究展示了使用Tableau结合语义网络分析的有用视觉分析,使用了在区块链域中通过Twitter的情感流和战略沟通策略的示例。我们比较调查了声誉好公司和声誉差公司之间的情绪流动和语言使用模式。此外,本研究还探讨了声誉与营销传播策略之间的关系。我们发现,当公众需求增加、交易增加以及代币价格高企时,加密货币公司会更积极地提供信息。社交媒体上的情感语言策略并没有影响加密货币的声誉。声誉好的公司和声誉差的公司的关键词语义表示模式相似。然而,声誉良好的公司就广泛的主题进行沟通,并使用更注重文化的策略,并通过扩大其与其他社交媒体网络的联系,更多地利用社交媒体营销的优势。可视化的大数据分析提供了对商业智能的洞察,有助于制定明智的政策。
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 去求助
来源期刊
自引率
0.00%
发文量
0
审稿时长
8 weeks
期刊最新文献
Correlation between virtual reality’s intervention and monitored brain activity: A systematic review Unfamiliar or Defamiliarization: The Uncanny Valley in Interactive Artwork Installations Consequences of Advertising Literacy among College Students Perception of Digital Restoration and Representation of Cultural Heritage -Focusing on Simulation and Simulacra Item Development to Predict the Driving Risk of Older Drivers using the Delphi Method
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1