An Overview of Social Media Apps and their Potential Role in Geospatial Research
Social media apps provide analysts with a wide range of data to study behavioral aspects of our everyday lives and to answer societal questions. Although social media data analysis is booming, only a handful of prominent social media apps, such as Twitter, Foursquare/Swarm, Facebook, or LinkedIn are...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-09-01
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| Series: | ISPRS International Journal of Geo-Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2220-9964/9/9/526 |
| _version_ | 1797554813741826048 |
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| author | Innocensia Owuor Hartwig H. Hochmair |
| author_facet | Innocensia Owuor Hartwig H. Hochmair |
| author_sort | Innocensia Owuor |
| collection | DOAJ |
| description | Social media apps provide analysts with a wide range of data to study behavioral aspects of our everyday lives and to answer societal questions. Although social media data analysis is booming, only a handful of prominent social media apps, such as Twitter, Foursquare/Swarm, Facebook, or LinkedIn are typically used for this purpose. However, there is a large selection of less known social media apps that go unnoticed in the scientific community. This paper reviews 110 social media apps and assesses their potential usability in geospatial research through providing metrics on selected characteristics. About half of the apps (57 out of 110) offer an Application Programming Interface (API) for data access, where rate limits, fee models, and type of spatial data available for download vary strongly between the different apps. To determine the current role and relevance of social media platforms that offer an API in academic research, a search for scientific papers on Google Scholar, the Association for Computing Machinery (ACM) Digital Library, and the Science Core Collection of the Web of Science (WoS) is conducted. This search revealed that Google Scholar returns the highest number of documents (Mean = 183,512) compared to ACM (Mean = 1895) and WoS (Mean = 1495), and that data and usage patterns from prominent social media apps are more frequently analyzed in research studies than those of less known apps. The WoS citation database was also used to generate lists of themes covered in academic publications that analyze the 57 social media platforms that offer an API. Results show that among these 57 platforms, for 26 apps at least some papers evolve around a geospatial discipline, such as Geography, Remote Sensing, Transportation, or Urban Planning. This analysis, therefore, connects apps with commonly used research themes, and together with tabulated API characteristics can help researchers to identify potentially suitable social media apps for their research. Word clouds generated from titles and abstracts of papers associated with the 57 platforms, grouped into seven thematic categories, show further refinement of topics addressed in the analysis of social media platforms. Considering various evaluation criteria, such as provision of geospatial data or the number (i.e., absence) of currently published research papers in connection with a social media platform, the study concludes that among the numerous social media apps available today, 17 less known apps deserve closer examination since they might be used to investigate previously underexplored research topics. It is hoped that this study can serve as a reference for the analysis of the social media landscape in the future. |
| first_indexed | 2024-03-10T16:38:24Z |
| format | Article |
| id | doaj.art-03f8b83aa4ec4e72ad27aa7976d4026a |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-10T16:38:24Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-03f8b83aa4ec4e72ad27aa7976d4026a2023-11-20T12:13:07ZengMDPI AGISPRS International Journal of Geo-Information2220-99642020-09-019952610.3390/ijgi9090526An Overview of Social Media Apps and their Potential Role in Geospatial ResearchInnocensia Owuor0Hartwig H. Hochmair1Geomatics Program, Fort Lauderdale Research and Education Center, University of Florida, 3205 College Ave, Davie, FL 33314, USAGeomatics Program, Fort Lauderdale Research and Education Center, University of Florida, 3205 College Ave, Davie, FL 33314, USASocial media apps provide analysts with a wide range of data to study behavioral aspects of our everyday lives and to answer societal questions. Although social media data analysis is booming, only a handful of prominent social media apps, such as Twitter, Foursquare/Swarm, Facebook, or LinkedIn are typically used for this purpose. However, there is a large selection of less known social media apps that go unnoticed in the scientific community. This paper reviews 110 social media apps and assesses their potential usability in geospatial research through providing metrics on selected characteristics. About half of the apps (57 out of 110) offer an Application Programming Interface (API) for data access, where rate limits, fee models, and type of spatial data available for download vary strongly between the different apps. To determine the current role and relevance of social media platforms that offer an API in academic research, a search for scientific papers on Google Scholar, the Association for Computing Machinery (ACM) Digital Library, and the Science Core Collection of the Web of Science (WoS) is conducted. This search revealed that Google Scholar returns the highest number of documents (Mean = 183,512) compared to ACM (Mean = 1895) and WoS (Mean = 1495), and that data and usage patterns from prominent social media apps are more frequently analyzed in research studies than those of less known apps. The WoS citation database was also used to generate lists of themes covered in academic publications that analyze the 57 social media platforms that offer an API. Results show that among these 57 platforms, for 26 apps at least some papers evolve around a geospatial discipline, such as Geography, Remote Sensing, Transportation, or Urban Planning. This analysis, therefore, connects apps with commonly used research themes, and together with tabulated API characteristics can help researchers to identify potentially suitable social media apps for their research. Word clouds generated from titles and abstracts of papers associated with the 57 platforms, grouped into seven thematic categories, show further refinement of topics addressed in the analysis of social media platforms. Considering various evaluation criteria, such as provision of geospatial data or the number (i.e., absence) of currently published research papers in connection with a social media platform, the study concludes that among the numerous social media apps available today, 17 less known apps deserve closer examination since they might be used to investigate previously underexplored research topics. It is hoped that this study can serve as a reference for the analysis of the social media landscape in the future.https://www.mdpi.com/2220-9964/9/9/526APIdata accessfee modelsGoogle ScholarWeb of ScienceACM Digital Library |
| spellingShingle | Innocensia Owuor Hartwig H. Hochmair An Overview of Social Media Apps and their Potential Role in Geospatial Research ISPRS International Journal of Geo-Information API data access fee models Google Scholar Web of Science ACM Digital Library |
| title | An Overview of Social Media Apps and their Potential Role in Geospatial Research |
| title_full | An Overview of Social Media Apps and their Potential Role in Geospatial Research |
| title_fullStr | An Overview of Social Media Apps and their Potential Role in Geospatial Research |
| title_full_unstemmed | An Overview of Social Media Apps and their Potential Role in Geospatial Research |
| title_short | An Overview of Social Media Apps and their Potential Role in Geospatial Research |
| title_sort | overview of social media apps and their potential role in geospatial research |
| topic | API data access fee models Google Scholar Web of Science ACM Digital Library |
| url | https://www.mdpi.com/2220-9964/9/9/526 |
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