Journal Article10.1016/J.COMPENVURBSYS.2018.05.007
Mining location from social media: A systematic review
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TL;DR: This analysis of 690 papers across 20 social media platforms, focussing particularly on the method used for extraction of location information, discusses and compare extraction methods, and considers their accuracy and coverage.
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About: This article is published in Computers, Environment and Urban Systems. The article was published on 30 May 2018. The article focuses on the topics: Social media.
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Delineating urban park catchment areas using mobile phone data: A case study of Tokyo
ChengHe Guan,ChengHe Guan,Jihoon Song,Jihoon Song,Michael Keith,Yuki Akiyama,Ryosuke Shibasaki,Taisei Sato +7 more
TL;DR: The application of mobile phone location data can improve the understanding of an urban park catchment area, provide useful information and methods to analyze the usage of urban parks, and can aid in the planning and policy-making of urban Parks.
Environmental Sustainability assessment 2.0: The value of social media data for determining the emotional responses of people to river pollution—A case study of Weibo (Chinese Twitter)
Siqing Shan,Jing Peng,Yigang Wei +2 more
TL;DR: Wang et al. as discussed by the authors investigated the emotional responses of people according to four dimensions: trends, seasons, space and dynamics (TSSD), and found that negative responses were much more common than positive ones across all seasons, 22.8% and 9.2%, respectively.
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References
Exploring Celebrities on Inferring User Geolocation in Twitter
Mohammad Ebrahimi,Mohammad Ebrahimi,Elaheh ShafieiBavani,Elaheh ShafieiBavani,Raymond K. Wong,Raymond K. Wong,Fang Chen,Fang Chen +7 more
- 23 May 2017
TL;DR: A novel approach based on the notion of celebrities to infer the location of Twitter users by categorizing highly-mentioned users (celebrities) into local and global, and consequently utilizing local celebrities as a major location indicator for inference.
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Multimodal geo-tagging in social media websites using hierarchical spatial segmentation
Pascal Kelm,Sebastian Schmiedeke,Thomas Sikora +2 more
- 06 Nov 2012
TL;DR: A hierarchical, multi-modal approach for estimating the GPS information that makes use of external resources like gazetteers to extract toponyms in the metadata and of visual and textual features to identify similar content.
From Interest to Location: Neighbor-Based Friend Recommendation in Social Media
Jin-Qi Zhu,Li Lu,Chun-Mei Ma +2 more
TL;DR: This work proposes a new concept named neighbor-based friend recommendation (NBFR), and proposes to model the user interest with multiple topics under the hypercube structure for friend recommendation, and offers a topic matching shortcut algorithm for more extensive recommendation.
7
Location Prediction via Social Contents and Behaviors: Location-Aware Behavioral LDA
Anna Tigunova,JooYoung Lee,Sadegh Nobari +2 more
- 14 Nov 2015
TL;DR: A generative model, called Location-aware Behavioral LDA (La-LDA), that is not only addressing what are topics of interest in social content, but also linking topics with 1) user interactions, and 2) locations is proposed.
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Learning the trip suggestion from landmark photos on the web
Rongrong Ji,Ling-Yu Duan,Jie Chen,Yang Shuang,Hongxun Yao,Tiejun Huang,Wen Gao +6 more
- 29 Dec 2011
TL;DR: A novel touristic trip suggestion system to facilitate the traveling of mobile users in a given city, which can suggest a shortest trip path that visits as many popular landmarks as possible through a shortest path search.
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