Mining social media for Understanding Women behavior
|Name||Mining social media for Understanding Women behavior|
Women’s informal conversations on social media (e.g. Twitter, Facebook) shed light into their daily work experiences—opinions, feelings, and concerns about the learning process. Data from such un-instrumented environments can provide valuable knowledge to inform Women’s learning. Analyzing such data, however, can be challenging. The complexity of Women’s experiences reflected from social media content requires human interpretation. However, the growing scale of data demands automatic data analysis techniques. In this paper, we developed a workflow to integrate both qualitative analysis and large-scale data mining techniques. We focus on engineering Women’s Twitter posts to understand issues and problems in their Daily work Experiences.
|ieee paper year||2014|