中文    English

Journal of library and information science in agriculture ›› 2020, Vol. 32 ›› Issue (10): 47-55.doi: 10.13998/j.cnki.issn1002-1248.2020.10.20-0434

• Research paper • Previous Articles     Next Articles

An Investigation into the Travel Information Needs of Online Q&A Platform Users: Taking Tuniu Q&A Community as an Example

ZHAO Xueqin, WANG Qingqing   

  1. School of History and Culture, Hubei University, Wuhan 430062
  • Received:2020-05-27 Online:2020-10-05 Published:2020-11-20

Abstract: [Purpose/Significance] In order to optimize online community services, attract and encourage more people with travel intentions to use the Internet to share and obtain travel information, this paper studies the travel information needs of users in the tourism Q&A community. [Method/Process] Firstly, by using the network text mining, we selected the Q&A content about Beijing from the Tuniu Q&A platform as a corpus. Secondly, we used two different keyword extraction algorithms: TF-IDF and TextRank to extract the keywords of each text. Finally, we constructed a co-occurrence network through Gephi and use Gephi's clustering function to clarify the theme of the keywords, so as to grasp the user's travel information needs. [Results/Conclusions] The travel information needs of users in the online travel Q&A community can be roughly divided into 7 categories: accommodation information, food information, traffic information, scenic spot information, group tour information, climate information and planning suggestions. Users have different types of travel information demands which are not separate and independent from each other. There is a staggered relationship between different demands.

Key words: online question and answer platform, network text mining, travel information demand

CLC Number: 

  • G250
[1] 2019文旅融合风向哪儿吹[N]. 中国消费者报, 2019-02-01(4).
[2] 中国互联网信息中心. 第44次中国互联网络发展状况统计报告[EB/OL].[2019-08-30]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/201908/P020190830356787490958.pdf.
[3] 金守郡. 旅游学概论[M]. 上海: 上海交通大学出版社, 2010: 6.
[4] CHU R.What online Hong Kong travelers look for on airline/travel websites?[J]. International journal of hospitality management, 2001, 20(1): 95-100.
[5] XIANG Z, PAN B.Travel queries on cities in the united states: Implications for search engine marketing for tourist destinations[J]. Tourism management, 2011, 32(1): 88-97.
[6] CHOI S, LEHTO X Y, OLEARY J T.What does the consumer want from a DMO website? A study of US and Canadian tourists & apos perspectives[J]. International journal of tourism research, 2007, 9(2): 59-72.
[7] 李君轶, 杨敏. 西安国内游客旅游网络信息搜索行为研究[J]. 经济地理, 2010, 30(7): 1212-1216, 1220.
[8] 张晓晖. 在线问答社区用户社交网络特征对其知识贡献数量的影响研究[D]. 山东大学, 2019.
[9] SHAH C, OH S, OH J S.Research agenda for social Q & A[J]. Library & information science research, 2009, 31(4): 205-209.
[10] 文彤, 邱佳佳. 旅游虚拟社区网络演化特征分析—以“马蜂窝”为例[J]. 地理与地理信息科学, 2018, 34(6): 119-126.
[11] 胡兴报. 国内旅游者网络旅游信息搜寻动机与行为研究[D]. 芜湖: 安徽师范大学, 2011.
[12] 胡梦迪. 在线旅游问答社区答案信息采纳影响因素研究[D]. 武汉: 武汉大学, 2018.
[13] 夏文. 用户对旅游虚拟社区的持续使用意愿研究[D]. 杭州: 浙江工商大学, 2019.
[14] 阮光册. 基于领域本体实现Web文本挖掘研究[J]. 图书情报工作, 2011, 55(18): 116-120.
[15] 夏立新, 楚林, 王忠义, 等. 基于网络文本挖掘的就业知识需求关系构建[J]. 图书情报知识, 2016(1): 94-100.
[16] 夏天. 词向量聚类加权TextRank的关键词抽取[J]. 数据分析与知识发现, 2017, 1(2): 28-34.
[17] OTTE E, ROUSSEAU R.Social network analysis: a powerful strategy, also for the information sciences[J]. Journal of information science, 28(6), 2002: 441-453.
[18] 张坤, 李晶, 王文韬, 等. 我国分享经济领域热点主题的可视化研究——基于共词分析和社会网络分析[J]. 图书馆, 2017(12): 66-71.
[19] 牟冬梅, 郑晓月, 王萍, 等. 社会网络分析在学科知识结构研究上的方法思辨[J]. 情报理论与实践, 2016, 39(8): 22-27.
[20] 卓群. 基于共词网络的社交媒体话题演化分析[J]. 情报科学, 2015, 33(1): 120-125.
[21] 钱宇星, 周华阳, 周利琴, 等. 老年在线社区用户健康信息需求挖掘研究[J]. 现代情报, 2019, 39(6): 59-69.
[22] 代金晶. 弹幕视频网站信息组织优化研究—以哔哩哔哩为例[J]. 图书馆研究与工作, 2019(7): 23-26, 52.
[1] XU Tongyang, DOU Lijuan. Library Knowledge Service Empowered by Smart Data and Synthetic Data [J]. Journal of library and information science in agriculture, 2026, (): 1-11.
[2] KOU Leilei, ZHU Zhongming, WANG Sili. Construction and Application of Complex Historical Event Evolution Graph Enabled by AI [J]. Journal of library and information science in agriculture, 2026, (): 1-13.
[3] WU Yuhao, ZHOU Zhigang, LIU Wei. Data Collaborative Governance Mechanism of Smart Libraries Driven by Application Scenarios [J]. Journal of library and information science in agriculture, 2026, (): 1-14.
[4] LIU Wei, JIN Jiaqin. Library Transformation in the Age of AI Agents: Service Reconfiguration and Governance Framework Based on the OpenClaw Architecture [J]. Journal of library and information science in agriculture, 2026, 38(4): 13-22.
[5] GUO Jinbo. Effects of AIGC on Reader Trust in Library Information [J]. Journal of library and information science in agriculture, 2026, 38(4): 84-98.
[6] HAN Shu. Health Information Service Quality Evaluation of Public Libraries under the Healthy China Strategy Using DeepSeek [J]. Journal of library and information science in agriculture, 2026, (): 1-13.
[7] DING Shuxin, HE Ziming, ZHANG Ke, YANG Ruixian. Structural Characteristics and Evolutionary Patterns of Smart Library Technology Innovation in China: A Multi-dimensional Empirical Analysis Based on Patent Mining [J]. Journal of library and information science in agriculture, 2026, (): 1-16.
[8] ZHUANG Jiayu. Factors Influencing Users' Intentions to Adopt AI Intelligent Services in Public Libraries: An Empirical Study Based on TAM and PLS-SEM [J]. Journal of library and information science in agriculture, 2026, (): 1-11.
[9] ZHANG Yanyi. Metaverse Construction for Medical Science Popularization Services in Libraries from an Embodied Cognition Perspective [J]. Journal of library and information science in agriculture, 2026, (): 1-13.
[10] ZHANG Yuxiang, CUI Lirui, XIN Chengguo. Community-Driven Governance in Diamond Open Access: Operational Mechanisms, Practical Challenges, and the Chinese Pathway [J]. Journal of library and information science in agriculture, 2026, (): 1-10.
[11] MIAO Meijuan, LUO Zhe, FENG Ruohan, LIU Jie. Development Models and Optimization Pathways of New Rural Public Cultural Spaces [J]. Journal of library and information science in agriculture, 2026, 38(3): 65-75.
[12] JIN Jiaqin. Exploring Practical Paths for the "Last Mile" of Public Digital Cultural Services: An Investigation Based on the Construction of the National Public Culture Cloud Platform [J]. Journal of library and information science in agriculture, 2026, 38(3): 55-64.
[13] LI Mei, YIN Mingzhang. Application Scenario-Driven Construction and Evaluation on Smart Service Models for Multi-Source and Cross-Modal Information Resources in University Libraries [J]. Journal of library and information science in agriculture, 2026, (): 1-12.
[14] HUANG Xiaotang, YAO Qibin. Collaborative Development Path of GLAM Institutions Based on AIGC Technology Application [J]. Journal of library and information science in agriculture, 2026, 38(2): 66-78.
[15] WU Yuhao, LIU Yihao, LI Qingjun, HU Xu. Open Sharing of Library Data Based on Large Language Models: Logic, Path and Strategy [J]. Journal of library and information science in agriculture, 2026, 38(1): 28-43.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!