The Journal of Machine Learning Research
Enriching the knowledge sources used in a maximum entropy part-of-speech tagger
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Recognizing contextual polarity in phrase-level sentiment analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Online Social Support: The Interplay of Social Networks and Computer-Mediated Communication
Online Social Support: The Interplay of Social Networks and Computer-Mediated Communication
Cheap and fast---but is it good?: evaluating non-expert annotations for natural language tasks
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
An unsupervised dynamic Bayesian network approach to measuring speech style accommodation
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
Proceedings of the 17th ACM international conference on Supporting group work
Discovering habits of effective online support group chatrooms
Proceedings of the 17th ACM international conference on Supporting group work
Shifting dynamics or breaking sacred traditions?: the role of technology in twelve-step fellowships
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Patterns of support in an online community for smoking cessation
Proceedings of the 6th International Conference on Communities and Technologies
On participation in group chats on Twitter
Proceedings of the 22nd international conference on World Wide Web
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
A comparison of social, learning, and financial strategies on crowd engagement and output quality
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
Social factors that contribute to attrition in MOOCs
Proceedings of the first ACM conference on Learning @ scale conference
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Today many people with serious diseases use online support groups to seek social support. For these groups to be sustained and effective, member retention and commitment is important. Our study examined how different types and amounts of social support in an online cancer support group are associated with participants' length of membership. We first built machine learning models to automatically identify the extent to which messages contained emotional and informational support. Agreement with human judges was high (r 0.76). We then used these models to measure the support exchanged in 1.5 million messages. Finally, we applied quantitative event history analysis to assess how exposure to emotional and informational support predicted group members' length of subsequent participation. The results demonstrated that the more emotional support members were exposed to, the lower the risk of dropout. In contrast, informational support did not have the same strong effects on commitment. We speculate that emotional support enhanced members' relationships with one another or the group as a whole, whereas informational support satisfied members' short-term information needs.