Understanding Social Influence in Activity Location Choice and Lifestyle Patterns Using Geolocation Data from Social Media

Samiul Hasan · Satish V. Ukkusuri · Xianyuan Zhan

33 citations0/0 files storedFrontiers in ICT

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Human Mobility and Location-Based Analysis Complex Network Analysis Techniques Data Management and Algorithms

Abstract

Social media check-in services have enabled people to share their activity-related choices providing a new source of human activity and social networks data. Geo-location data from these services offers us information, in new ways, to understand social influence on individual choices. In this paper, we investigate the extent of social influence on individual activity and life-style choices from social media check-in data. We first collect user check-ins and their social network information by linking two social media systems (Twitter and Foursquare) and analyze the structure of the underlying social network. We next infer user check-in and geo life-style patterns using topic models. We analyze the correlation between the social relationships and individual-level patterns. We investigate whether or not two individuals have similar activity choice and geo life-style patterns if they are socially connected. We find that the similarity between two users, in their check-in behavior and life-style patterns, increases with the increase of the friendship probability.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 33 citations exist upstream.

References

2009Power-Law Distributions in Empirical Data 2018Power-law distributions in empirical data 2011Friendship and mobility 2021Exploring Millions of Footprints in Location Sharing Services 2012A Tale of Many Cities: Universal Patterns in Human Urban Mobility 2005The effects of attitudes and personality traits on mode choice 2004What type of vehicle do people drive? The role of attitude and lifestyle in influencing vehicle type choice 2014Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data

Cited by

2020Visualization, Spatiotemporal Patterns, and Directional Analysis of Urban Activities Using Geolocation Data Extracted from LBSN 2018ICT, activity space–time and mobility: new insights, new models, new methodologies 2019Spatiotemporal Analysis to Observe Gender Based Check-In Behavior by Using Social Media Big Data: A Case Study of Guangzhou, China 2019Destination choice modeling using location-based social media data 2017Deriving human activity from geo-located data by ontological and statistical reasoning

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.