Abstract
Social media data provides researchers with insight into how social media platforms are used, and how they shape the lives of their respective users. While exploring and analyzing data has vast research potential, the process for doing so is tedious, time-consuming, and difficult, especially for non-technical researchers. In most cases, researchers require funds and technical personnel to even begin exploring data-related ideas. For those that do have the resources, low quality and high latency data is typically the end result. To decrease the overall gap between the data and the researcher, we propose a method and prototypical web-based system that utilizes Twitter’s latest API offering to enable researchers to collect high quality data themselves at minimal cost. The system has been evaluated through multiple implementations at multiple universities. Our initial findings are positive, indicating that our design and prototype alleviate the major issues faced by non-technical researchers collecting social media data.
Recommended Citation
Kishore, Shohil; Peko, Gabrielle; and Sundaram, David, "Looking Through the Twitter Glass: Bridging the Data – Researcher Gap" (2019). AMCIS 2019 Proceedings. 4.
https://aisel.aisnet.org/amcis2019/social_computing/social_computing/4
Looking Through the Twitter Glass: Bridging the Data – Researcher Gap
Social media data provides researchers with insight into how social media platforms are used, and how they shape the lives of their respective users. While exploring and analyzing data has vast research potential, the process for doing so is tedious, time-consuming, and difficult, especially for non-technical researchers. In most cases, researchers require funds and technical personnel to even begin exploring data-related ideas. For those that do have the resources, low quality and high latency data is typically the end result. To decrease the overall gap between the data and the researcher, we propose a method and prototypical web-based system that utilizes Twitter’s latest API offering to enable researchers to collect high quality data themselves at minimal cost. The system has been evaluated through multiple implementations at multiple universities. Our initial findings are positive, indicating that our design and prototype alleviate the major issues faced by non-technical researchers collecting social media data.