Applied sentiment analysis on a real estate advertisement recommendation model

Regina Fang Ying Lin; Jiesheng Wu; Kuo Kun Tseng; Yuk Ming Tang; Lu Liu

doi:10.1080/17517575.2022.2037158

Applied sentiment analysis on a real estate advertisement recommendation model

Regina Fang Ying Lin (Corresponding Author)
, Jiesheng Wu
, Kuo Kun Tseng (Corresponding Author)
, Yuk Ming Tang
, Lu Liu

Research output: Journal article publication › Journal article › Academic research › peer-review

8 Citations (Scopus)

Abstract

Recently, the data generated are exploding in the information age. In the post-COVID-19 era, some real estate contracts have been signed online, and online advertisement recommendation has become a new way to reduce the searching cost. Therefore, the model in which real estate online recommendations can be made suitable without user preferences has become a tricky problem. This study uses sentiment and economic data to predict real estate sales and then made an advertisement recommendation from the forecast results. The 2SA-RERec (Two Sentiment Analysis of Real Estate Recommendation) model is proposed, which shows the highest accuracy among the others.

Original language	English
Article number	2037158
Number of pages	29
Journal	Enterprise Information Systems
Volume	17
Issue number	6
DOIs	https://doi.org/10.1080/17517575.2022.2037158
Publication status	Published - Jun 2023

Keywords

back-propagation neural network
grey system theory
Real estate online advertisement recommendation model
seasonal and trend decomposition using loess
sentiment analysis

ASJC Scopus subject areas

Computer Science Applications
Information Systems and Management

More information

10.1080/17517575.2022.2037158

Cite this

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title = "Applied sentiment analysis on a real estate advertisement recommendation model",

abstract = "Recently, the data generated are exploding in the information age. In the post-COVID-19 era, some real estate contracts have been signed online, and online advertisement recommendation has become a new way to reduce the searching cost. Therefore, the model in which real estate online recommendations can be made suitable without user preferences has become a tricky problem. This study uses sentiment and economic data to predict real estate sales and then made an advertisement recommendation from the forecast results. The 2SA-RERec (Two Sentiment Analysis of Real Estate Recommendation) model is proposed, which shows the highest accuracy among the others.",

keywords = "back-propagation neural network, grey system theory, Real estate online advertisement recommendation model, seasonal and trend decomposition using loess, sentiment analysis",

author = "Lin, \{Regina Fang Ying\} and Jiesheng Wu and Tseng, \{Kuo Kun\} and Tang, \{Yuk Ming\} and Lu Liu",

note = "Funding Information: We thank Shenzhen Government for generously providing the funding for this research [JCYJ20190806144609107, HA11409015, and 20,200,829,144,221,001]. We also thank the anonymous referees for their comments and guidance. All errors are ours. Publisher Copyright: {\textcopyright} 2022 Informa UK Limited, trading as Taylor \& Francis Group.",

year = "2023",

month = jun,

doi = "10.1080/17517575.2022.2037158",

language = "English",

volume = "17",

journal = "Enterprise Information Systems",

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AU - Lin, Regina Fang Ying

AU - Wu, Jiesheng

AU - Tseng, Kuo Kun

AU - Tang, Yuk Ming

AU - Liu, Lu

N1 - Funding Information: We thank Shenzhen Government for generously providing the funding for this research [JCYJ20190806144609107, HA11409015, and 20,200,829,144,221,001]. We also thank the anonymous referees for their comments and guidance. All errors are ours. Publisher Copyright: © 2022 Informa UK Limited, trading as Taylor & Francis Group.

PY - 2023/6

Y1 - 2023/6

N2 - Recently, the data generated are exploding in the information age. In the post-COVID-19 era, some real estate contracts have been signed online, and online advertisement recommendation has become a new way to reduce the searching cost. Therefore, the model in which real estate online recommendations can be made suitable without user preferences has become a tricky problem. This study uses sentiment and economic data to predict real estate sales and then made an advertisement recommendation from the forecast results. The 2SA-RERec (Two Sentiment Analysis of Real Estate Recommendation) model is proposed, which shows the highest accuracy among the others.

AB - Recently, the data generated are exploding in the information age. In the post-COVID-19 era, some real estate contracts have been signed online, and online advertisement recommendation has become a new way to reduce the searching cost. Therefore, the model in which real estate online recommendations can be made suitable without user preferences has become a tricky problem. This study uses sentiment and economic data to predict real estate sales and then made an advertisement recommendation from the forecast results. The 2SA-RERec (Two Sentiment Analysis of Real Estate Recommendation) model is proposed, which shows the highest accuracy among the others.

KW - back-propagation neural network

KW - grey system theory

KW - Real estate online advertisement recommendation model

KW - seasonal and trend decomposition using loess

KW - sentiment analysis

UR - https://www.scopus.com/pages/publications/85125948476

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DO - 10.1080/17517575.2022.2037158

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Applied sentiment analysis on a real estate advertisement recommendation model

Abstract

Keywords

ASJC Scopus subject areas

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