Webcare via openbare en privé sociale media

Daphne Hachmang, R. V. Os, M. Akpınar, E. Pool
{"title":"Webcare via openbare en privé sociale media","authors":"Daphne Hachmang, R. V. Os, M. Akpınar, E. Pool","doi":"10.5117/tvt2019.2.003.hach","DOIUrl":null,"url":null,"abstract":"\n \n \n Webcare via public and private social media. A corpus study on the effect of Conversational Human Voice in the PT sector\n \n \n This study investigates the use of Conversational Human Voice (CHV) by a Dutch Public Transport (PT) operator in reactive webcare conversations with travelers on private and public social media channels and the effect of this use on the traveler’s sentiment during the conversation. In this study, CHV is unraveled into eight aspects. 244 conversations were analyzed, selected from the PT-operator’s public and private social media channels. Messages sent by the PT companies were coded for CHV; messages of travelers were coded for sentiment. The aspects organization responds as an individual and informal language were used the most often by the PT operator. Use of CHV is similar on private social networks and public social networks, with the exception of organization responds as an individual (used more on private social networks) and language to compensate the lack of non-verbal communication (used more on public social networks). Furthermore, results show that the use of sympathy has a positive effect on the traveler’s sentiment.","PeriodicalId":192335,"journal":{"name":"Tijdschrift voor Taalbeheersing","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tijdschrift voor Taalbeheersing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5117/tvt2019.2.003.hach","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Webcare via public and private social media. A corpus study on the effect of Conversational Human Voice in the PT sector This study investigates the use of Conversational Human Voice (CHV) by a Dutch Public Transport (PT) operator in reactive webcare conversations with travelers on private and public social media channels and the effect of this use on the traveler’s sentiment during the conversation. In this study, CHV is unraveled into eight aspects. 244 conversations were analyzed, selected from the PT-operator’s public and private social media channels. Messages sent by the PT companies were coded for CHV; messages of travelers were coded for sentiment. The aspects organization responds as an individual and informal language were used the most often by the PT operator. Use of CHV is similar on private social networks and public social networks, with the exception of organization responds as an individual (used more on private social networks) and language to compensate the lack of non-verbal communication (used more on public social networks). Furthermore, results show that the use of sympathy has a positive effect on the traveler’s sentiment.
通过公共和私人社交媒体进行网络护理。本研究调查了荷兰公共交通(PT)运营商在私人和公共社交媒体渠道上与旅行者进行被动网络护理对话时使用对话式人声(CHV),以及这种使用对谈话过程中旅行者情绪的影响。在本研究中,CHV被分解为八个方面。分析了244个对话,这些对话选自pt运营商的公共和私人社交媒体渠道。PT公司发送的信息以CHV编码;旅行者的信息是根据情感编码的。组织作为个体响应的方面和非正式语言是PT操作员最常使用的。在私人社交网络和公共社交网络上,CHV的使用是相似的,除了作为个人的组织回应(在私人社交网络上使用得更多)和语言来弥补非语言交流的不足(在公共社交网络上使用得更多)。此外,结果表明,同情的使用对旅行者的情绪有积极的影响。
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:604180095
Book学术官方微信