In this study, we examined the impact of demographics and relationship status on posting a revealing picture of oneself as a profile picture on Facebook. We randomly sampled and coded 1,000 profiles of Israeli Facebook users ranging in age between 18 and 61 years. Over 40% of the profiles showed at least 1 picture of the user dressed in a skimpy outfit. Results of a multiple logistic regression model indicated that younger age, a lower level of education, and not being engaged in a committed romantic relationship were significant predictors of the posting of these pictures. Further, gender alone was not a significant predictor, but the interaction of gender and level of education was. Specifically, women with a high-schoollevel education posted revealing pictures of themselves more often than did men with a similar level of education. We analyzed our results in light of Goffman's theory of self-presentation.

Recommender systems for news articles on social media select and filter content through automatic personalization. As a result, users are often unaware of opposing points of view, leading to informational blindspots and potentially polarized opinions. They may be aware of a topic, but only be exposed to one viewpoint on this topic. However, recommender systems have just as much potential to help users find a plurality of viewpoints. In this spirit, this paper introduces an approach to automatically identifying content that represents a wider range of opinions on a given topic. Our offline results show positive results for our distance measure with regard to diversification on topic and channel. However, our user study results confirm that user acceptance of this diversification also needs to be addressed in tandem to enable a complete solution.