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Cyclicity of real estate-related trends: topic modelling and sentiment analysis on German real estate news
Journal of European Real Estate Research Pub Date : 2021-07-01 , DOI: 10.1108/jerer-12-2020-0059
Franziska Ploessl , Tobias Just , Lino Wehrheim

Purpose

The purpose of this paper is to identify and analyse the news coverage and sentiment of real estate-related trends in Germany. Trends are considered as being stable and long-term. If the news coverage and sentiment of trends underlie cyclicity, this could impact investors’ behaviour. For instance, in the case of increased reporting on sustainability issues, investors may be inclined to invest more in sustainable buildings, assuming that this is of growing importance to their clients. Hence, investors could expect higher returns when a trend topic goes viral.

Design/methodology/approach

With the help of topic modelling, incorporating seed words partially generated via word embeddings, almost 170,000 newspaper articles published between 1999 and 2019 by a major German real estate news provider are analysed and assigned to real estate-related trends. Through applying a dictionary-based approach, this dataset is then analysed based on whether the tone of the news coverage of a specific trend is subject to change.

Findings

The articles concerning urbanisation and globalisation account for the largest shares of reporting. However, the shares are subject to change over time, both in terms of news coverage and sentiment. In particular, the topic of sustainability illustrates a clearly increasing trend with cyclical movements throughout the examined period. Overall, the digitalisation trend has a highly positive connotation within the analysed articles, while regulation displays the most negative sentiment.

Originality/value

To the best of the authors’ knowledge, this is the first application to explore German real estate newspaper articles regarding the methodologies of word representation and seeded topic modelling. The integration of topic modelling into real estate analysis provides a means through which to extract information in a standardised and replicable way. The methodology can be applied to several further fields like analysing market reports, company statements or social media comments on real estate topics. Finally, this is also the first study to measure the cyclicity of real estate-related trends by means of textual analysis.



中文翻译:

房地产相关趋势的周期性:德国房地产新闻的主题建模和情感分析

目的

本文的目的是识别和分析德国房地产相关趋势的新闻报道和情绪。趋势被认为是稳定和长期的。如果新闻报道和趋势情绪是周期性的基础,这可能会影响投资者的行为。例如,在可持续性问题报告增加的情况下,投资者可能倾向于更多地投资于可持续建筑,假设这对他们的客户越来越重要。因此,当趋势话题传播开来时,投资者可以期待更高的回报。

设计/方法/方法

在主题建模的帮助下,结合部分通过词嵌入生成的种子词,对德国一家主要房地产新闻提供商在 1999 年至 2019 年间发表的近 170,000 篇报纸文章进行了分析,并将其分配给了与房地产相关的趋势。通过应用基于字典的方法,然后根据特定趋势的新闻报道的基调是否会发生变化来分析该数据集。

发现

有关城市化和全球化的文章占报道的最大份额。但是,在新闻报道和情绪方面,这些股票可能会随着时间的推移而发生变化。尤其是,可持续性主题在整个审查期间呈现出明显增加的趋势,周期性运动。总体而言,数字化趋势在所分析的文章中具有高度积极的内涵,而监管则表现出最消极的情绪。

原创性/价值

据作者所知,这是第一个探索关于词表示和种子主题建模方法的德国房地产报纸文章的应用程序。将主题建模集成到房地产分析中提供了一种以标准化和可复制的方式提取信息的方法。该方法可以应用于其他几个领域,例如分析市场报告、公司声明或有关房地产主题的社交媒体评论。最后,这也是首次通过文本分析来衡量房地产相关趋势的周期性的研究。

更新日期:2021-07-01
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