Cyclicity of real estate-related trends: topic modelling and sentiment analysis on German real estate news

Abstract

PurposeThe 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/approachWith 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.FindingsThe 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/valueTo 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.

Changes in warehouse spatial patterns and rental prices: Are they related? Exploring the case of US metropolitan areas

“…Therefore, we have performed an automated web data extraction method: web scraping. Individual scripts were developed to scrape the warehouse information from the Html file and assemble one dataset for each metropolitan area (Ge et al, 2021;Gharahighehi et al, 2021;Jiao et al, 2021;Luo and He, 2021;Pineda-Jaramillo and Pineda-Jaramillo, 2021;Ploessl et al, 2021). This method was mainly composed of seven steps for this paper: (i) find the URL where the data is published; (ii) inspect the webpage to find the data from its source code; (iii) build the prototype code, which was written in R language and using the rvest package and intended to extract and prepare the data; (iv) generalize the code considering functions, loops and debugging and run the code alternating among US metropolitan areas; (v) store the data as an organized data frame; (vi) check and clean the gathered data; (vii) geocode the information on each warehouse.…”

News coverage vs sentiment: evaluating German residential real estate markets

“…These generative probabilistic models primarily concern the derivation of underlying common topics. However, there is limited research that applies topic modelling in the context of real estate market analysis: Ploessl et al (2021) used seeded LDA for the assignment of German news articles to six real estate-related trends and revealed that both the news coverage and sentiment of these expected stable trends show cyclical elements within a 21-year period. Another algorithm, the structural topic model, was used by Koelbl et al (2021) for the detection of risk-factors in the 10-K filings of REITs to investigate how these could affect the risk perceptions of investors.…”

Real Estate Research Trends and Directions in Africa:

“…This kind of study is also critical for consolidating emerging research activities and trends as a means for mapping out the direction of knowledge development in the sector. Thus, while real estate research is increasingly gaining momentum, the AfRES has neglected exploring the contributions of academic writings as a body of knowledge and additional source (Nguyen, et al, 2021;Ploessl et al, 2021;. The African Real Estate Society has promoted networking, research, and education among property professionals across Africa and has hosted annual conferences since its formation in 1997.…”

“…This study investigates the real estate research trends and directions emerging from the proceedings of AfRES conferences between 2011 and 2022. To achieve this aim, the study answers the following questions: Other similar studies (Breuer and Nadler, 2012;Abatecola et al, 2013;Nguyen et al, 2021;Just et al, 2021) that have looked at research contributions within the International Real Estate Society (IRES) structure have also focused only on the American Real Estate Society, (ARES) and European Real Estate Society (ERES). They note a disproportionate focus on empirical studies within the finance and investment themes.…”