Social- Semantic Analysis of Social Media Interactions to assess customer satisfaction in transit agencies
社交媒体交互的社会语义分析,以评估公交机构的客户满意度
基本信息
- 批准号:536827-2018
- 负责人:
- 金额:$ 1.75万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Collaborative Research and Development Grants
- 财政年份:2020
- 资助国家:加拿大
- 起止时间:2020-01-01 至 2021-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The aim of this proposed study is to progress the discipline of social media analytics in transit through developing an integrated and interactive model with emphasis on the interplay between social and semantic (and their sentiment) network parameters. The aim is to provide transit agencies with means to understand the topics of debate or issues of concerns or interest by different groups of riders based on their interactions on Twitter and Facebook. That is: who is talking about what topics at different times? Do the topics discussed relate to recent events, communications, or changes to the transit system? This is essential to better profiling customers and their levels of satisfaction as a step towards understanding behavior patterns and drivers. Equally important, this is essential for effective communication and outreach that can help reduce the typically negative input by customers on social media.
The results of the research will be used to build a customizable analytics portal in the form of an adaptive dashboard for use by Transit staff to analyze social media contents. It is expected that a staff member will start by choosing a social media outlet or account to analyze. The system will then allow the user to select several semantic and social parameters to study. The system will also allow the user to select and customize periodical reports to track trends. The use of machine learning in conducting such analysis can yield valuable insights to system planners and operators.
这项研究的目的是通过开发一个集成的和交互式的模型,重点是社会和语义(及其情感)网络参数之间的相互作用,在运输过程中的社会媒体分析的学科进展。其目的是为运输机构提供手段,根据不同乘客群体在Twitter和Facebook上的互动,了解他们辩论的主题或关注或感兴趣的问题。也就是说:谁在不同的时间谈论什么话题?讨论的主题是否与最近的事件、通信或交通系统的变化有关?这对于更好地分析客户及其满意度至关重要,这是了解行为模式和驱动因素的一步。同样重要的是,这对于有效的沟通和推广至关重要,可以帮助减少客户在社交媒体上的负面输入。
研究结果将用于以自适应仪表板的形式构建可定制的分析门户,供公交工作人员分析社交媒体内容。预计工作人员将首先选择一个社交媒体渠道或账户进行分析。然后,该系统将允许用户选择几个语义和社会参数进行研究。该系统还将允许用户选择和定制定期报告,以跟踪趋势。 在进行此类分析时使用机器学习可以为系统规划者和运营商提供有价值的见解。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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ElDiraby, Tamer其他文献
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Social- Semantic Analysis of Social Media Interactions to assess customer satisfaction in transit agencies
社交媒体交互的社会语义分析,以评估公交机构的客户满意度
- 批准号:
536827-2018 - 财政年份:2019
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$ 1.75万 - 项目类别:
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