Perceiving Residents’ Festival Activities Based on Social Media Data: A Case Study in Beijing, China

Social media data contains real-time expressed information, including text and geographical location. As a new data source for crowd behavior research in the era of big data, it can reflect some aspects of the behavior of residents. In this study, a text classification model based on the BERT and Tr...

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Main Authors: Bingqing Wang, Bin Meng, Juan Wang, Siyu Chen, Jian Liu
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:ISPRS International Journal of Geo-Information
Subjects:
Online Access:https://www.mdpi.com/2220-9964/10/7/474
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spelling doaj-55a403822ba448b8b492d3ff3640f50f2021-07-23T13:45:03ZengMDPI AGISPRS International Journal of Geo-Information2220-99642021-07-011047447410.3390/ijgi10070474Perceiving Residents’ Festival Activities Based on Social Media Data: A Case Study in Beijing, ChinaBingqing Wang0Bin Meng1Juan Wang2Siyu Chen3Jian Liu4College of Applied Arts and Sciences, Beijing Union University, No. 197 Beitucheng West Road, Beijing 100191, ChinaCollege of Applied Arts and Sciences, Beijing Union University, No. 197 Beitucheng West Road, Beijing 100191, ChinaCollege of Applied Arts and Sciences, Beijing Union University, No. 197 Beitucheng West Road, Beijing 100191, ChinaCollege of Applied Arts and Sciences, Beijing Union University, No. 197 Beitucheng West Road, Beijing 100191, ChinaCollege of Resource Environment and Tourism, Capital Normal University, No. 105 West 3rd Ring Road North, Beijing 100048, ChinaSocial media data contains real-time expressed information, including text and geographical location. As a new data source for crowd behavior research in the era of big data, it can reflect some aspects of the behavior of residents. In this study, a text classification model based on the BERT and Transformers framework was constructed, which was used to classify and extract more than 210,000 residents’ festival activities based on the 1.13 million Sina Weibo (Chinese “Twitter”) data collected from Beijing in 2019 data. On this basis, word frequency statistics, part-of-speech analysis, topic model, sentiment analysis and other methods were used to perceive different types of festival activities and quantitatively analyze the spatial differences of different types of festivals. The results show that traditional culture significantly influences residents’ festivals, reflecting residents’ motivation to participate in festivals and how residents participate in festivals and express their emotions. There are apparent spatial differences among residents in participating in festival activities. The main festival activities are distributed in the central area within the Fifth Ring Road in Beijing. In contrast, expressing feelings during the festival is mainly distributed outside the Fifth Ring Road in Beijing. The research integrates natural language processing technology, topic model analysis, spatial statistical analysis, and other technologies. It can also broaden the application field of social media data, especially text data, which provides a new research paradigm for studying residents’ festival activities and adds residents’ perception of the festival. The research results provide a basis for the design and management of the Chinese festival system.https://www.mdpi.com/2220-9964/10/7/474social media datafestival activitiescitizen perceptionsword frequency analysistopic analysis
collection DOAJ
language English
format Article
sources DOAJ
author Bingqing Wang
Bin Meng
Juan Wang
Siyu Chen
Jian Liu
spellingShingle Bingqing Wang
Bin Meng
Juan Wang
Siyu Chen
Jian Liu
Perceiving Residents’ Festival Activities Based on Social Media Data: A Case Study in Beijing, China
ISPRS International Journal of Geo-Information
social media data
festival activities
citizen perceptions
word frequency analysis
topic analysis
author_facet Bingqing Wang
Bin Meng
Juan Wang
Siyu Chen
Jian Liu
author_sort Bingqing Wang
title Perceiving Residents’ Festival Activities Based on Social Media Data: A Case Study in Beijing, China
title_short Perceiving Residents’ Festival Activities Based on Social Media Data: A Case Study in Beijing, China
title_full Perceiving Residents’ Festival Activities Based on Social Media Data: A Case Study in Beijing, China
title_fullStr Perceiving Residents’ Festival Activities Based on Social Media Data: A Case Study in Beijing, China
title_full_unstemmed Perceiving Residents’ Festival Activities Based on Social Media Data: A Case Study in Beijing, China
title_sort perceiving residents’ festival activities based on social media data: a case study in beijing, china
publisher MDPI AG
series ISPRS International Journal of Geo-Information
issn 2220-9964
publishDate 2021-07-01
description Social media data contains real-time expressed information, including text and geographical location. As a new data source for crowd behavior research in the era of big data, it can reflect some aspects of the behavior of residents. In this study, a text classification model based on the BERT and Transformers framework was constructed, which was used to classify and extract more than 210,000 residents’ festival activities based on the 1.13 million Sina Weibo (Chinese “Twitter”) data collected from Beijing in 2019 data. On this basis, word frequency statistics, part-of-speech analysis, topic model, sentiment analysis and other methods were used to perceive different types of festival activities and quantitatively analyze the spatial differences of different types of festivals. The results show that traditional culture significantly influences residents’ festivals, reflecting residents’ motivation to participate in festivals and how residents participate in festivals and express their emotions. There are apparent spatial differences among residents in participating in festival activities. The main festival activities are distributed in the central area within the Fifth Ring Road in Beijing. In contrast, expressing feelings during the festival is mainly distributed outside the Fifth Ring Road in Beijing. The research integrates natural language processing technology, topic model analysis, spatial statistical analysis, and other technologies. It can also broaden the application field of social media data, especially text data, which provides a new research paradigm for studying residents’ festival activities and adds residents’ perception of the festival. The research results provide a basis for the design and management of the Chinese festival system.
topic social media data
festival activities
citizen perceptions
word frequency analysis
topic analysis
url https://www.mdpi.com/2220-9964/10/7/474
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