Analyses on the Spatial Distribution Characteristics of Urban Rental Housing Supply and Demand Hotspots Based on Social Media Data

The Chinese Time-honored Catering Brands (CTCBs) in the five northwestern provinces are the accumulation of culture in the northwest of China and have precious value. Their formation and development process have their own characteristics and rules. In order to clarify the spatial distribution characteristics and influencing factors of CTCBs in these provinces, this study uses geolocated social media data (the data of the CTCBs’ directory, location, and per capita consumption level), and applies statistical analysis, kernel density analysis, standard deviational ellipse, and buffer analysis to analyze the spatial distribution characteristics and influencing factors of CTCBs in the five northwestern provinces. The results show that: (1) the spatial development intensity of CTCBs is relatively strong in their original place, and their spatial distribution is uneven. The overall distribution is in the northwest-southeast direction, with strong agglomeration, and tends to be scattered in the periphery of the agglomeration area. There are some areas with higher concentrations distributed in the form of patches. (2) The number and spatial distribution of old brands with different grades and tastes have different characteristics. (3) The spatial distribution pattern of CTCBs is formed under a variety of factors, such as historical and traditional culture, regional traffic conditions and urban development patterns, etc.

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Citizens, Elites, and Social Media Methodological Challenges and Opportunities in the Study of Persuasion and Mobilization

The Oxford Handbook of Electoral Persuasion ◽

10.1093/oxfordhb/9780190860806.013.27 ◽

2019 ◽

pp. 1036-1058

Author(s):

Philip Habel ◽

Yannis Theocharis

Keyword(s):

Social Media ◽

Big Data ◽

Supply And Demand ◽

Political Process ◽

The Political ◽

The Novel ◽

Complete Understanding ◽

Social Media Data ◽

Challenges And Opportunities ◽

Media Data

In the last decade, big data, and social media in particular, have seen increased popularity among citizens, organizations, politicians, and other elites—which in turn has created new and promising avenues for scholars studying long-standing questions of communication flows and influence. Studies of social media play a prominent role in our evolving understanding of the supply and demand sides of the political process, including the novel strategies adopted by elites to persuade and mobilize publics, as well as the ways in which citizens react, interact with elites and others, and utilize platforms to persuade audiences. While recognizing some challenges, this chapter speaks to the myriad of opportunities that social media data afford for evaluating questions of mobilization and persuasion, ultimately bringing us closer to a more complete understanding Lasswell’s (1948) famous maxim: “who, says what, in which channel, to whom, [and] with what effect.”

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A Comparative Study of Spatial and Temporal Preferences for Waterfronts in Wuhan based on Gender Differences in Check-In Behavior

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi8090413 ◽

2019 ◽

Vol 8 (9) ◽

pp. 413 ◽

Cited By ~ 3

Author(s):

Wu ◽

Li ◽

Ma

Keyword(s):

Gender Differences ◽

Social Media ◽

Geographical Location ◽

Distribution Characteristics ◽

Social Media Data ◽

Men And Women ◽

Male And Female ◽

Points Of Interest ◽

And Gender ◽

Media Data

The geographical location and check-in frequency of social platform users indicate their personal preferences and intentions for space. On the basis of social media data and gender differences, this study analyzes Weibo users’ preferences and the reasons behind these preferences for the waterfronts of the 21 major lakes within Wuhan’s Third Ring Road, in accordance with users’ check-in behaviors. According to the distribution characteristics of the waterfronts’ points of interest, this study explores the preferences of male and female users for waterfronts and reveals, through the check-in behaviors of Weibo users, the gender differences in the preference and willingness of these users to choose urban waterfronts. Results show that men and women check in significantly more frequently on weekends than on weekdays. Women are more likely than men to check in at waterfronts. Significant differences in time and space exist between male and female users’ preferences for different lakes.

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Spatio-Temporal Patterns of Fitness Behavior In Beijing Based on Social Media Data

10.21203/rs.3.rs-967228/v1 ◽

2021 ◽

Author(s):

Tian Bin ◽

Meng Bin ◽

Zhi Guoqing ◽

Qi Zhenyu ◽

Chen Siyu ◽

...

Keyword(s):

Social Media ◽

Spatial Distribution ◽

Latent Dirichlet Allocation ◽

Temporal Distribution ◽

Temporal Patterns ◽

Social Media Data ◽

Periodic Distribution ◽

Spatio Temporal ◽

Southern City ◽

Media Data

Abstract Using social media data, this paper employs FastAI, Latent Dirichlet Allocation (LDA) and other text mining techniques coupled with GIS spatial analysis methods to study temporal and spatial patterns of fitness behavior of residents in Beijing, China, from the perspective of residents’ daily behavior. Using LDA theme model technology, it is found that fitness activities can be divided into four types: running-based fitness; riding-based fitness; fitness in sports venue; and fitness under professional guidance. Emotional analysis revealed that, residents can get a better fitness experience in sports venues. There are also obvious differences in the spatio-temporal distribution of the different fitness behaviors. Fitness behavior of Beijing residents has a multi-center spatial distribution pattern, with a wide coverage in northern city areas but obvious aggregation areas in southern city areas. In terms of temporal patterns, the residents' fitness frequency shows an obvious periodic distribution (weekly and 24 hours). And there are obvious differences in the time distribution of fitness behaviors for each theme. Additionally, based on the attribution analysis of a geodetector, it is found that the spatial distribution of fitness behavior of residents is mainly affected by factors such as catering services, education and culture, companies and public facilities.

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