Get Online Support, Feel Better -- Sentiment Analysis and Dynamics in an Online Cancer Survivor Community

Qiu, Baojun; Zhao, Kang; Mitra, Prasenjit; Wu, Dinghao; Caragea, Cornelia; Yen, John; Greer, Greta E.; Portier, Kenneth M.

doi:10.1109/passat/socialcom.2011.127

Cited by 78 publications

(74 citation statements)

References 16 publications

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“…For example, Kim et al [6] analyzed emotional expressions that arise in online Q&A discussions and relate them to types of discussions, such as resolved vs. unresolved discussions. Qiu et al [10] analyzes trends of sentiment expressions in cancer forums using a sentiment word list and emoticons. Our work focuses on relating sentiment expressions with degrees of responses generated by the community.…”

Section: Supporting Theory and Related Workmentioning

confidence: 99%

Role of Sentiment in Message Propagation: Reply vs. Retweet Behavior in Political Communication

Kim

Yoo

2012

2012 International Conference on Social Informatics

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This paper examines the role of sentiment in information propagation. We make use of political communication in the Twitter space, and relate emotion expressions in a message to the degrees of responses generated by the message. We also compare differences between user reply vs. retweet behavior with respect to sentiment variables. The current results indicate that that degree of emotion expressions in twitter messages can affect the number of replies generated as well as retweet rates. Due to the difference in the nature of endorsement (retweet) vs. responses (replies or conversation), some of the variables present opposite roles in explaining the degree of responses the message receives. We expect these results will help generating a predictive model of message propagation.

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Section: Supporting Theory and Related Workmentioning

confidence: 99%

Role of Sentiment in Message Propagation: Reply vs. Retweet Behavior in Political Communication

Kim

Yoo

2012

2012 International Conference on Social Informatics

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“…Research has found that such support can help patients adjust to the stress of living with and fighting against their diseases [5,6,7] and is a consistent indicator of survival [8]. An OHC also serves as an outlet for users' emotional needs and improve their offline life [9].…”

Section: Introductionmentioning

confidence: 99%

Social Support and User Engagement in Online Health Communities

Wang

Zhao

Street

2014

Lecture Notes in Computer Science

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Abstract. Online health communities (OHCs) have become a major source of social support for people with health problems. Members of OHCs interact online with those who face similar problems and are involved in different types of social supports, such as informational support, emotional support and companionship. Using a case study of an OHC among breast cancer survivors, we first use machine learning techniques to reveal the types of social support embedded in each post from an OHC. Then we generate each user's contribution profile by aggregating the user's involvement in various types of social support and reveal that users play different roles in the OHC. By comparing online activities for users with different roles and conducting survival analysis on users' time span of online activities, we illustrate that users' levels of engagement in an OHC are related to various types of social support in different ways.

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“…It has been shown that those who started a thread in a cancer OHC often show a more positive sentiment in their posts later in the thread, after other OHC members provided replies Qiu et al (2011);Portier et al (2013).…”

Section: Online Health Communitiesmentioning

confidence: 99%

Proceedings of the Fifth Workshop on Cognitive Modeling and Computational Linguistics

2014

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followed in the tradition of earlier CMCL meetings, providing a venue for research in mathematical and computational psycholinguistics. We solicited papers on a broad spectrum of topics which spanned the formal modeling of language representation, development, and processing, and were very pleased to receive 17 submissions this year. The program below includes 8 of these papers which were selected for final presentation at the workshop. We would like to thank all submitting authors for the quality and variety of the papers we received, and for helping to foster the growth of the field of computational psycholinguistics. We would also like to thank our program committee for providing expertise in the evaluation of submitted papers. Finally, our program this year includes invited talks by Dr. Naomi Feldman of the University of Maryland and Dr. Edward Gibson of the Massachusetts Institute of Technology. We extend our appreciation to these researchers for sharing their work with us. Eye-movements in reading exhibit frequency spillover effects: fixation durations on a word are affected by the frequency of the previous word. We explore the idea that this effect may be an emergent property of a computationally rational eyemovement strategy that is navigating a tradeoff between processing immediate perceptual input, and continued processing of past input based on memory. We present an adaptive eye-movement control model with a minimal capacity for such processing, based on a composition of thresholded sequential samplers that integrate information from noisy perception and noisy memory. The model is applied to the List Lexical Decision Task and shown to yield frequency spillover-a robust property of human eye-movements in this task, even with parafoveal masking. We show that spillover in the model emerges in approximately optimal control policies that sometimes process memory rather than perception. We compare this model with one that is able to give priority to perception over memory, and show that the perception-priority policies in such a model do not perform as well in a range of plausible noise settings. We explain how the frequency spillover arises from a counter-intuitive but fundamental property of sequenced thresholded samplers. Introduction and overviewOur interest is in understanding how eyemovements are controlled in service of linguistic tasks involving reading-more specifically, how saccadic decisions are conditioned on the moment-by-moment state of incremental perceptual and cognitive processing. The phenomena we are concerned with here are spillover effects, where fixation durations on a word are affected by linguistic properties of the prior word or words. The specific idea we explore is that spillover effects may be emergent properties of a computationally rational control strategy that is navigating a tradeoff between processing immediate perceptual input, and continued processing of past input based on a memory of recent stimuli. The paper is organized as follows. We first review evidence that eye-m...

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Get Online Support, Feel Better -- Sentiment Analysis and Dynamics in an Online Cancer Survivor Community

Cited by 78 publications

References 16 publications

Role of Sentiment in Message Propagation: Reply vs. Retweet Behavior in Political Communication

Role of Sentiment in Message Propagation: Reply vs. Retweet Behavior in Political Communication

Social Support and User Engagement in Online Health Communities

Proceedings of the Fifth Workshop on Cognitive Modeling and Computational Linguistics

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