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

A reinforcement sensitivity perspective on adolescents' susceptibility to the influence of soap opera viewing on alcohol attitudes

Previous research found support for an association between exposure to alcohol-related media content and alcohol attitudes, intentions and behavior. Nevertheless, research on what makes young people susceptible to the occurrence of this relationship is scarce. The current study examined the behavioral activation (BAS) and inhibition system (BIS) as moderators of the relationship between soap opera viewing and alcohol attitudes. A cross-sectional survey was carried out among a sample of 922 adolescents (M-age=14.96years, SD=.85, 56% girls). Regression analyses showed no association between total television viewing and alcohol attitudes, but did confirm that soap opera viewing is associated with positive attitudes towards alcohol use. Moderation analyses indicated that BAS did not moderate this relationship, while BIS did; the relationship between soap opera viewing and positive attitudes toward alcohol was only significant for adolescents with a low BIS-profile. These results provide support for the premise that an elevated BIS protects adolescents from the effect of soap opera viewing frequency on their alcohol attitudes

Digital learning resources and ubiquitous technologies in education

This research explores the educators' attitudes and perceptions about their utilisation of digital learning technologies. The methodology integrates measures from ‘the pace of technological innovativeness’ and the ‘technology acceptance model’ to understand the rationale for further ICT investment in compulsory education. A quantitative study was carried out amongst two hundred forty-one educators in Malta. It has investigated the costs and benefits of using digital learning resources in schools from the educator’s perspective. Principal component analysis has indicated that the educators were committed to using digital technologies. In addition, a step-wise regression analysis has shown that the younger teachers were increasingly engaging in digital learning resources. Following this study’s empirical findings educational stakeholders are better informed about how innovative technologies can support our students. In conclusion, this paper puts forward key implications and recommendations for regulatory authorities and policy makers for better curricula and educational outcomes.peer-reviewe

Social Bots for Online Public Health Interventions

According to the Center for Disease Control and Prevention, in the United States hundreds of thousands initiate smoking each year, and millions live with smoking-related dis- eases. Many tobacco users discuss their habits and preferences on social media. This work conceptualizes a framework for targeted health interventions to inform tobacco users about the consequences of tobacco use. We designed a Twitter bot named Notobot (short for No-Tobacco Bot) that leverages machine learning to identify users posting pro-tobacco tweets and select individualized interventions to address their interest in tobacco use. We searched the Twitter feed for tobacco-related keywords and phrases, and trained a convolutional neural network using over 4,000 tweets dichotomously manually labeled as either pro- tobacco or not pro-tobacco. This model achieves a 90% recall rate on the training set and 74% on test data. Users posting pro- tobacco tweets are matched with former smokers with similar interests who posted anti-tobacco tweets. Algorithmic matching, based on the power of peer influence, allows for the systematic delivery of personalized interventions based on real anti-tobacco tweets from former smokers. Experimental evaluation suggests that our system would perform well if deployed. This research offers opportunities for public health researchers to increase health awareness at scale. Future work entails deploying the fully operational Notobot system in a controlled experiment within a public health campaign

Regression and Learning to Rank Aggregation for User Engagement Evaluation

User engagement refers to the amount of interaction an instance (e.g., tweet, news, and forum post) achieves. Ranking the items in social media websites based on the amount of user participation in them, can be used in different applications, such as recommender systems. In this paper, we consider a tweet containing a rating for a movie as an instance and focus on ranking the instances of each user based on their engagement, i.e., the total number of retweets and favorites it will gain. For this task, we define several features which can be extracted from the meta-data of each tweet. The features are partitioned into three categories: user-based, movie-based, and tweet-based. We show that in order to obtain good results, features from all categories should be considered. We exploit regression and learning to rank methods to rank the tweets and propose to aggregate the results of regression and learning to rank methods to achieve better performance. We have run our experiments on an extended version of MovieTweeting dataset provided by ACM RecSys Challenge 2014. The results show that learning to rank approach outperforms most of the regression models and the combination can improve the performance significantly.Comment: In Proceedings of the 2014 ACM Recommender Systems Challenge, RecSysChallenge '1

Social capital and social media: the effects of Facebook use on social capital and perceived community involvement

The purpose of this paper is to look at the effect of social media use on social capital. This paper attempts to establish a dichotomy between 'real' and 'perceived' social capital and the effect of social media use on both. I use a survey instrument measuring both the social media use and `real' social capital of one group compared with the social media use and `perceived' social capital of the second group. I find that while social media use is related with survey respondents feeling more involved politically and in their community, there is no correlation between actual political/community involvement for other respondents

Utility of Parental Mediation Model on Youth’s Problematic Online Gaming

The Parental Mediation Model PMM) was initially designed to regulate children’s attitudes towards the traditional media. In the present era, because of prevalent online media there is a need for similar regulative measures. Spending long hours on social media and playing online games increase the risks of exposure to the negative outcomes of online gaming. This paper initially applied the PMM developed by European Kids Online to (i) test the reliability and validity of this model and (ii) identify the effectiveness of this model in controlling problematic online gaming (POG). The data were collected from 592 participants comprising 296 parents and 296 students of four foreign universities, aged 16 to 22 years in Kuala Lumpur (Malaysia). The study found that the modified model of the five-factor PMM (Technical mediation, Monitoring mediation, Restrictive mediation, Active Mediation of Internet Safety, and Active mediation of Internet Use) functions as a predictor for mitigating POG. The findings suggest the existence of a positive relation between ‘monitoring’ and ‘restrictive’ mediation strategies and exposure to POG while Active Mediation of Internet Safety and Active mediation of Internet use were insignificant predictors. Results showed a higher utility of ‘technical’ strategies by the parents led to less POG. The findings of this study do not support the literature suggesting active mediation is more effective for reducing youth’s risky behaviour. Instead, parents need to apply more technical mediations with their children and adolescents’ Internet use to minimize the negative effects of online gaming