Sensing Subjective Well-being from Social Media

Subjective Well-being(SWB), which refers to how people experience the quality of their lives, is of great use to public policy-makers as well as economic, sociological research, etc. Traditionally, the measurement of SWB relies on time-consuming and costly self-report questionnaires. Nowadays, people are motivated to share their experiences and feelings on social media, so we propose to sense SWB from the vast user generated data on social media. By utilizing 1785 users' social media data with SWB labels, we train machine learning models that are able to "sense" individual SWB from users' social media. Our model, which attains the state-by-art prediction accuracy, can then be used to identify SWB of large population of social media users in time with very low cost.Comment: 12 pages, 1 figures, 2 tables, 10th International Conference, AMT 2014, Warsaw, Poland, August 11-14, 2014. Proceeding

The influence of teacher emotion on grading practices: A preliminary look at the evaluation of student writing

The evaluation of student work is a central aspect of the teaching profession that can affect students in significant ways. Although teachers use multiple criteria for assessing student work, it is not yet known if emotions are a factor in their grading decisions as has been found in other instances of professional evaluations. Reason to believe that this might be the case not only comes from emotion-congruent judgment research, but also from the emerging field of teacher emotion research which is beginning to reveal that emotion may be an important element in various teacher cognitions and practices. The present study provides initial evidence that emotions may bias the grades teachers assign to their students, such that positive and negative emotions influence grade assignment in emotion-congruent ways. This research offers empirical contributions to research on emotion and cognition as well as on teacher emotion. © 2013 © 2013 Taylor & Francis