Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Faculty of Construction and Environment | en_US |
| dc.contributor | Department of Land Surveying and Geo-Informatics | en_US |
| dc.contributor.advisor | Shi, Wen-zhong (LSGI) | - |
| dc.creator | Zhang, Junwei | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/10524 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Spatial, temporal and semantic analysis of instagram for community discovery in Hong Kong | en_US |
| dcterms.abstract | Abundant research using Participatory Sensing Systems have brought a new perspective for understanding city. The social media as a form of Participatory Sensing Systems, such as Twitter, Facebook, and Foursquare, are greatly used for various domains research in recent years. This study explores the spatial-temporal life pattern, and communities in Hong Kong using an increasingly popular social media, Instagram. The main objective of this research is to discover communities who share similar interests and spatial-temporal behaviors. An Instagram data segmentation scheme is designed for dividing applicable data for latter analysis. The posts with popular hashtag from active users are segmented for the community discovery. A new approach is proposed in this paper to identify clusters of user based on the topic-label, time-label, and geo-label inferred separately. Three topic models are developed through LDA modeling on the user hashtag corpus. Four types of time preferences are identified using k-means clustering on the user-time matrix. Eight types of urban function are classified and quantitatively visualized using digital map POI. The mixture of urban function in Hong Kong are mapped and discussed. Communities are identified and their characteristics are explored, which indicates the strong connections and communications between Hong Kong Island and Kowloon. The high concentrations of industrial estate in these two regions are discussed at the end. | en_US |
| dcterms.extent | ix, 102 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2017 | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.LCSH | Online social networks -- China -- Hong Kong | en_US |
| dcterms.LCSH | Spatial behavior -- Social aspects -- Data processing | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 991022385849503411.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 3.11 MB | Adobe PDF | View/Open |
Copyright Undertaking
As a bona fide Library user, I declare that:
- I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
- I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
- I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.
By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.
Please use this identifier to cite or link to this item:
https://theses.lib.polyu.edu.hk/handle/200/10524