Spatial Characteristics of Twitter Users—Toward the Understanding of Geosocial Media Production
Social media is a rich source of spatial data but it has also many flaws and well-known limitations, especially in regard to representation and representativeness, since very little is known about the demographics of the user population. At the same time, the use of locational services, is in fact,...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-08-01
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| Series: | ISPRS International Journal of Geo-Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2220-9964/6/8/236 |
| _version_ | 1819267071540723712 |
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| author | Michal Rzeszewski Lukasz Beluch |
| author_facet | Michal Rzeszewski Lukasz Beluch |
| author_sort | Michal Rzeszewski |
| collection | DOAJ |
| description | Social media is a rich source of spatial data but it has also many flaws and well-known limitations, especially in regard to representation and representativeness, since very little is known about the demographics of the user population. At the same time, the use of locational services, is in fact, dependent on those characteristics. We address this gap in knowledge by exploring divides between Twitter users, based on the spatial and temporal distribution of the content they produce. We chose five cities and data from 2015 to represent different socio-spatial contexts. Users were classified according to spatial and non-spatial measures: home range estimation; standard distance; nearest neighbor index, and; proposed localness index. There are distinct groups of geosocial media producers, which suggests that such datasets cannot be treated as uniform representations. We found a positive correlation between spatial behavior and posting activity. It is suggested that there are universal patterns of behavior that are conditioned by software services—the example of Foucauldian “technologies of self”. They can also represent the dominance of the most prolific users over the whole data stream. Results are discussed in the context of the importance and role of user location in social media. |
| first_indexed | 2024-12-23T21:11:20Z |
| format | Article |
| id | doaj.art-cd1b2bc937fa429c97ef3a21b32ee72e |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-12-23T21:11:20Z |
| publishDate | 2017-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-cd1b2bc937fa429c97ef3a21b32ee72e2022-12-21T17:31:03ZengMDPI AGISPRS International Journal of Geo-Information2220-99642017-08-016823610.3390/ijgi6080236ijgi6080236Spatial Characteristics of Twitter Users—Toward the Understanding of Geosocial Media ProductionMichal Rzeszewski0Lukasz Beluch1Faculty of Geographical and Geological Sciences, Adam Mickiewicz University, Krygowskiego 10, 61-680 Poznan, PolandInstitute of Geography and Spatial Management, Jagiellonian University, 30-387 Cracow, PolandSocial media is a rich source of spatial data but it has also many flaws and well-known limitations, especially in regard to representation and representativeness, since very little is known about the demographics of the user population. At the same time, the use of locational services, is in fact, dependent on those characteristics. We address this gap in knowledge by exploring divides between Twitter users, based on the spatial and temporal distribution of the content they produce. We chose five cities and data from 2015 to represent different socio-spatial contexts. Users were classified according to spatial and non-spatial measures: home range estimation; standard distance; nearest neighbor index, and; proposed localness index. There are distinct groups of geosocial media producers, which suggests that such datasets cannot be treated as uniform representations. We found a positive correlation between spatial behavior and posting activity. It is suggested that there are universal patterns of behavior that are conditioned by software services—the example of Foucauldian “technologies of self”. They can also represent the dominance of the most prolific users over the whole data stream. Results are discussed in the context of the importance and role of user location in social media.https://www.mdpi.com/2220-9964/6/8/236geosocial mediaspatial behaviorTwitterpost-socialist |
| spellingShingle | Michal Rzeszewski Lukasz Beluch Spatial Characteristics of Twitter Users—Toward the Understanding of Geosocial Media Production ISPRS International Journal of Geo-Information geosocial media spatial behavior post-socialist |
| title | Spatial Characteristics of Twitter Users—Toward the Understanding of Geosocial Media Production |
| title_full | Spatial Characteristics of Twitter Users—Toward the Understanding of Geosocial Media Production |
| title_fullStr | Spatial Characteristics of Twitter Users—Toward the Understanding of Geosocial Media Production |
| title_full_unstemmed | Spatial Characteristics of Twitter Users—Toward the Understanding of Geosocial Media Production |
| title_short | Spatial Characteristics of Twitter Users—Toward the Understanding of Geosocial Media Production |
| title_sort | spatial characteristics of twitter users toward the understanding of geosocial media production |
| topic | geosocial media spatial behavior post-socialist |
| url | https://www.mdpi.com/2220-9964/6/8/236 |
| work_keys_str_mv | AT michalrzeszewski spatialcharacteristicsoftwitteruserstowardtheunderstandingofgeosocialmediaproduction AT lukaszbeluch spatialcharacteristicsoftwitteruserstowardtheunderstandingofgeosocialmediaproduction |