The booming Internet technology and media have generated large sets of social media data, with which the social sensing analyses based on users' reviews have become a research hotspot and have been increasingly applied in the study of urban park usage and perception. However, most existing studies adopt a single model for text data processing. To fill this gap, this study aims to compare social media text data analysis methods and assess their advantages, disadvantages and applicability in park perception research. The Lexicon-based classification analysis model (lexicon model) and LDA (Latent Dirichlet Allocation) model widely used in relevant research were selected. Based on text data obtained from public reviews of 10 urban parks in Beijing on Dianping, this study explored the perception topic distribution of each park and all parks in general, and compared the classification results of perception topics between these two models. Results show that the lexicon model is conducive to the parallel comparison of perception frequency between parks, while the LDA model can directly reflect each park's characteristics and visitors' perception preferences; the combined use of the two models can optimize park perception assessment. Results from the two methods reveal that visitors to urban parks in Beijing focused more on their social recreation needs and visual aesthetics brought by the natural landscape, as well as conditions of the transportation facilities and the consumption in the parks. This research can provide optimization suggestions for the selection and use of social media text analysis methods, and a basis and guidance for park construction and management improvement.
● Exploring the advantages, disadvantages, and applicability of two text analysis models
● The lexicon model is more suitable for parallel comparison between perceived objects by users
● The Latent Dirichlet Allocation (LDA) model can better capture the characteristics of each individual perceived object
● Taking advantage of the two models’ strengths is vital for optimizing landscape perception assessment
. [J]. Landscape Architecture Frontiers, 2023, 11(5): 8-21.
Zhenyu SHANG, Kexin CHENG, Yuqing JIAN, Zhifang WANG. Comparison and Applicability Study of Analysis Methods for Social Media Text Data: Taking Perception of Urban Parks in Beijing as an Example. Landsc. Archit. Front., 2023, 11(5): 8-21.
Air quality improvement, microclimate regulation, noise
Humidity, exposure, freshness, wind and sunshine
Biodiversity
Animals, plants
Swan, holly, dead wood, birdsong and floral fragrance
History and culture
Cultural and historical values, cultural heritage, historical sites
Qing Dynasty, relics, art, Dragon Boat Festival
Aesthetic appreciation
Scenery, beauty, inspiration
Flowers, photography, attractive, unpleasant
Education
Popularization of science, education
Knowledge, learned, knowledgeable, ignorant
Religion
Religious worship, belief, refuge
Rituals, Buddha beads, Taoism, enlightenment, marriage seeking
Physical and mental recovery
Relaxation, stress release, mind restoration
Soothing, beautiful, downcast, cheerful
Recreational activities
Outdoor activities, sports
Walking, boating, hiking, ball games
Social interaction
Social integration, interaction between individuals
Mom, dad, friends and relatives, gatherings
Tab.2
Fig.1
Fig.2
Fig.3
Park
Number of topics
Coherence score
Yuanmingyuan Park
10
0.5611
Yuyuantan Park
10
0.5216
Fragrant Hills Park
9
0.6049
Jingshan Park
9
0.6334
Beijing Shiyuan Park
9
0.5829
Chaoyang Park
10
0.5845
Beijing World Park
6
0.6577
Olympic Forest Park
10
0.5046
Badachu Park
9
0.6385
Beijing Garden Expo Park
8
0.5411
Tab.3
Yuanmingyuan Park
Yuyuantan Park
Fragrant Hills Park
Jingshan Park
Beijing Shiyuan Park
Topic 1
Transportation and tickets
Epidemic
Hiking activities
Cultural heritage
Natural landscape
Topic 2
Cultural relics
Cherry blossom festival
Park Introduction
Historical change
Service facilities
Topic 3
Garden landscape
Lupine view
Transportation and tickets
Park introduction
Social activities
Topic 4
Natural landscape
Cherry blossom view
Experiential perception
Featured flowers
Pavilion experience
Topic 5
Historical perception
Tickets and consumption
Cultural landscape
Featured constructions
Park introduction
Topic 6
Patriotic education
Natural landscape
Education and learning
Surrounding landscape
Music festival
Topic 7
Park introduction
Transportation facilities
Natural landscape
Epidemic
Service experience
Topic 8
Lotus flowers
Park introduction
The Forbidden City vision
Transportation and tickets
Topic 9
Featured ice-cream
Leisure and entertainment
Topic 10
Chaoyang Park
Beijing World Park
Olympic Forest Park
Badachu Park
Beijing Garden Expo Park
Topic 1
Transportation and tickets
Transportation and tickets
Leisure sports
Worship activities
Featured gardens
Topic 2
Service experience
Collective memory and perception
Transportation facilities
Leisure facilities
Aesthetic experience
Topic 3
Parent-child activities
Park introduction
Social activities
Buddhist landscape
Activity experience
Topic 4
Leisure and entertainment
Performances
Night show
Gatherings
Transportation facilities
Topic 5
Book market
Featured landscapes
Sporting activities
Hiking activities
Cultural activities
Topic 6
Park introduction
Summer and Autumn view
Park introduction
Leisure activities
Topic 7
Temple fair
Spring view
Collective memory and
Park introduction perception
Topic 8
Spring activities
Park introduction
Transportation facilities
Topic 9
Epidemic
Topic 10
Gatherings
Tab.4
Fig.4
Fig.5
LexiconLDA
Transportation and tickets
Spring view
Featured constructions
Religious culture
Hiking activities
Autumn view
Social activities
Collective memory and perception
Cultural history
Gatherings and performances
Environmental improvement
0.012
0.172
?0.088
?0.019
0.045
0.095
0.011
?0.054
?0.030
?0.059
Biodiversity
—**
0.200
?0.049
—**
?0.126
0.039
?0.088
0.020
0.041
0.008
History and culture
?0.076
?0.066
0.148
0.126
?0.050
?0.053
?0.131
0.049
0.248
—**
Aesthetic appreciation
?0.063
0.121
0.024
0.024
?0.078
0.125
?0.123
0.031
0.153
?0.057
Education
?0.026
0.069
0.141
0.045
?0.067
?0.050
?0.044
0.104
0.101
0.009
Religion
0.023
?0.070
0.010
0.182
0.183
?0.020
?0.038
?0.049
?0.051
0.046
Physical and mental recovery
—**
0.067
?0.063
?0.036
0.082
0.032
?0.002
0.017
?0.024
?0.050
Recreational activities
0.082
0.130
?0.100
?0.030
0.034
0.010
0.113
?0.081
?0.062
0.009
Social interaction
0.063
0.045
?0.043
?0.073
?0.025
?0.092
0.259
0.028
?0.157
0.050
Tab.5
Fig.6
Research subject
Lexicon model
LDA model
Perception topic classification
Advantages
1) Clear topic classification to make the topics different from each other and with specific contents 2) Effective identification of perception contents with limited attention 3) Analysis results available for parallel comparison between parks
More comprehensive, real-time reflection of visitors' perception contents
Disadvantages
Little consideration of the actual use of the park, resulting in a possible lack of perception contents
1) Lack of sensitivity to low-frequency perception topics due to failing to extract perception contents less frequently mentioned 2) Incapability of making parallel comparison between parks
Perception content identification
Advantages
Precise identification of the perception contents, covering topics with low perception frequency
1) Emphasis on the park characteristics, by a detailed classification of the perception topics with high awareness level 2) Clear perception contents to ensure quick identification of the topics
Disadvantages
1) Words extracted basing on the lexicon, for which the analysis results rely heavily on the completeness of the lexicon 2) Further manual interpretation of specific perception contents required
Relatively blurred boundaries between perception topics
Scope of application
Advantages
Suitable for regional-scale, multi-park perception analysis and inter-park comparison, with a comprehensive lexicon that can be adapted to different research objects
More effective perception analysis for individual parks
Disadvantages
Higher requirements for the lexicon to make it adjustable
Ambiguous results for regional-scale, multi-park perception analysis, making manual interpretation difficult
Tab.6
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