论文标题
Twitter上的采矿旅游经验：一个案例研究
Mining Tourism Experience on Twitter: A case study
论文作者
论文摘要
随着数字数据和社交网络平台的增加，社交媒体科学在推动与产品/服务功能和客户服务运营有关的公司决策方面的影响变得越来越重要。特别是，像Twitter这样的平台，人们可以分享几乎所有内容的经验，都可以极大地影响公司的声誉和奉献以及地点或旅游网站的声誉和奉献。在文献中研究和提出了文本挖掘工具，以获得价值并在Twitter上执行趋势主题和情感分析。由于数据是这些模型的燃料，因此“正确”的燃料，即与域相关的燃料会改变其准确性。在本文中，我们描述了通过与旅游相关的Twitter数据集执行的\ textit {dateOps / mlops}操作的管道，以理解旅游动机和兴趣。旅行/酒店业可以利用所获得的知识，以开发数据驱动的战略服务，以及可以消费有关旅游目的地的相关信息的旅行者。
With the increase of digital data and social network platforms the impact of social media science in driving company decision related to product/service features and customer care operations is becoming more crucial. In particular, platform such as Twitter where people can share experience about almost everything can drastically impact the reputation and offering of a company as well as of a place or tourism site. Text mining tools are researched and proposed in literature in order to gain value and perform trend topics and sentiment analysis on Twitter. As data are the fuels for these models, the "right" ones, i.e the domain-related ones makes a difference on their accuracy. In this paper, we describe a pipeline of \textit{DataOps / MLOps} operations performed over a tourism related Twitter dataset in order to comprehend tourism motivation and interest. The gained knowledge can be exploit, by the travel/hospitality industry in order to develop data-driven strategic service, and by travelers which can consume relevant information about tourist destination.
