Do people communicate about their whereabouts? Investigating the relation between user-generated text messages and Foursquare check-in places. Issue 3 (3rd July 2018)

• Record Type: Journal Article
• Authors: Li, Ming; Westerholt, Rene; Zipf, Alexander
• Is Part Of: Geo-spatial information science. Volume 21:Issue 3(2018)
• Page Start: 159
• Page End: 172
• Publication Date: 2018-07-03
• Subjects: Text mining -- latent semantic analysis -- semantic concepts -- Foursquare -- location-based social network (LBSN); Geographic information systems -- Periodicals; Cartography -- Data processing -- Periodicals; Surveying -- Data processing -- Periodicals; Remote sensing -- Periodicals; 526.0285
• DOI: 10.1080/10095020.2018.1498669
• Languages: English
• ISSNs: 1009-5020

Abstract

ABSTRACT: The social functionality of places (e.g. school, restaurant) partly determines human behaviors and reflects a region's functional configuration. Semantic descriptions of places are thus valuable to a range of studies of humans and geographic spaces. Assuming their potential impacts on human verbalization behaviors, one possibility is to link the functions of places to verbal representations such as users' postings in location-based social networks (LBSNs). In this study, we examine whether the heterogeneous user-generated text snippets found in LBSNs reliably reflect the semantic concepts attached with check-in places. We investigate Foursquare because its available categorization hierarchy provides rich a- priori semantic knowledge about its check-in places, which enables a reliable verification of the semantic concepts identified from user-generated text snippets. A latent semantic analysis is conducted on a large Foursquare check-in dataset. The results confirm that attached text messages can represent semantic concepts by demonstrating their large correspondence to the official Foursquare venue categorization. To further elaborate the representativeness of text messages, this work also performs an investigation on the textual terms to quantify their abilities of representing semantic concepts (i.e., representativeness ), and another investigation on semantic concepts to quantify how well they can be represented by text messages (i.e., representability ). The results shed light on featured terms with strong locational characteristics, as well as on distinctive semantic concepts with potentially strong impacts on human verbalizations.