Social Media Analytics
By Stefan Stieglitz, Linh Dang-Xuan, Axel Bruns, Christoph Neuberger. Business & Information Systems Engineering, 2014
304 citations recorded by the source corpus.
Subfields: Computer Science Applications, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/9bee728b12a1d762ce504a43076608c3cf5ee7c3
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Science Applications
In Computer Vision and Pattern Recognition
In Statistical and Nonlinear Physics
- Christian Sandström
- Christofer Laurell
- Christoph Neuberger
- Stefan Stieglitz
- Björn Ross
- Milad Mirbabaie
- José Ramón Saura
Citations in the corpus
- The sharing economy in social media: Analyzing tensions between market and non-market logics (2017, methodology): “This also means the researcher does not need to rely on often inaccurate digital data collection methods, such as scraping techniques (Stieglitz et al., 2014).”
- Digital Disruption beyond Uber and Airbnb—Tracking the long tail of the sharing economy (2020, methodology): “Drawing from the domain of big data analytics, SMA is an interdisciplinary approach that combines, extends, and adapts methods for analysis of social media data (Stieglitz et al., 2014; cf. Jung et al., 2017; Brem and Bilgram, 2015) that has been introduced as a methodological alternative relatively”
- Social media analytics - Challenges in topic discovery, data collection, and data preparation (2018, methodology): “The Social Media Analytics Framework (Stieglitz et al., 2014; Stieglitz & Dang-Xuan, 2013). restricting our search further to include only articles that mentioned one of the SMA steps in the abstract.”