管理评论

管理评论 ›› 2023, Vol. 35 ›› Issue (11): 153-165.

• 电子商务与信息管理 • 上一篇    下一篇

公众对假房源的关注点和态度：基于微博评论的文本挖掘研究

刘桂海1,2,3, 崔福龙1, 卢彩菡1, 曾文海1   

  1. 1. 江西师范大学城市建设学院, 南昌 330022;
    2. 江西师范大学不动产研究所, 南昌 330022;
    3. 江西师范大学管理科学与工程研究中心, 南昌 330022
  • 收稿日期:2022-10-04 出版日期:2023-11-28 发布日期:2023-12-27
  • 通讯作者: 曾文海(通讯作者),江西师范大学城市建设学院副教授,硕士生导师。
  • 作者简介:刘桂海,江西师范大学城市建设学院副教授,硕士生导师,博士,江西师范大学不动产研究所、管理科学与工程研究中心研究员;崔福龙,江西师范大学城市建设学院硕士研究生;卢彩菡,江西师范大学城市建设学院硕士研究生。
  • 基金资助:
    国家社会科学基金重大项目（20&ZD068）；江西省社会科学基金一般项目（21GL08；20GL06）；江西省教育厅科学技术研究项目（GJJ2200325）；江西省高等学校教学改革研究重点课题（JXJG-21-2-20）。

Public Concerns and Attitudes towards “Fake House Ads”: A Text Mining Study Based on Microblog Comments

Liu Guihai1,2,3, Cui Fulong1, Lu Caihan1, Zeng Wenhai1   

  1. 1. College of City Construction, Jiangxi Normal University, Nanchang 330022;
    2. Real Estate Research Center, Jiangxi Normal University, Nanchang 330022;
    3. Management Science and Engineering Research Center, Jiangxi Normal University, Nanchang 330022
  • Received:2022-10-04 Online:2023-11-28 Published:2023-12-27

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摘要： 基于文本挖掘技术对假房源微博评论展开深入分析，运用文本特征提取、词频分析、特征关联分析进行文本特征分析，再结合情感分析法完成情感倾向分析，挖掘出评论深层蕴意，探究公众真实的关注点、情感态度及其形成机理，可为公众优化行为策略、中介企业提升服务水平、管理部门转变监管模式提供参考。研究表明：（1）公众对于假房源和整体房源市场的情感以消极情感为主，达到了72.1%，且69.3%为高度消极情感。（2）公众对于房源的关注点为房源质量、服务水平、个体感知、监管力度四个方面，存在关注重心错位的现象。（3）诱发积极和消极情感产生的核心要素分别为房源质量、中介企业。其中，监管力度对积极情感产生的作用小于对消极情感产生的作用。（4）中介企业经营模式的选择影响着中介企业对于假房源的重视程度，间接影响了公众情感变化。以上结论对揭示假房源乱象本质、深挖公众真实内心需要、推动房地产市场良性发展具有重要启示意义。

关键词: 房源信息, 文本挖掘, 情感特征分析

Abstract: An in-depth analysis of fake house microblog commentary based on text mining technology, a text feature analysis by means of text feature extraction, word frequency analysis and feature association analysis, and an analysis of sentiment tendency, may help provide an insight into the deeper meaning of the commentary, the real concerns and sentimental attitude of the public, and the formation mechanism underlying the concerns and attitude. Such an insight enables the public to optimize their behavior strategies, intermediary enterprises to improve their services and authorities to change their supervision mode. The study shows that:(1) public sentiment towards fake house ads and the overall housing market is predominantly negative, as evidenced by 72.1% of the public holding a negative attitude and 69.3% holding a highly negative attitude; (2) there is a misalignment in the focus of public attention on the four levels of housing quality, service level, individual perception and supervision; (3) the core factors for whether the public sentiment is positive or negative lie in the quality of available houses and the level of intermediary service. The intensity of regulation plays a smaller role in generating positive sentiment than in generating negative sentiment; and (4) the choice of the business model of intermediary enterprises affects the degree of importance they attach to fake house ads, which indirectly affects the change in public sentiment. The above findings have implications for revealing the nature of fake house ads, digging deeper into the public's real inner needs and promoting the benign development of the real estate market.

Key words: housing information, text mining, sentiment feature analysis