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Background Online communities have been gaining popularity as support venues for chronic disease management. User engagement, information exposure, and social influence mechanisms can play a significant role in the utility of these platforms. Objective In this paper, we characterize peer interactions in an online community for chronic disease management. Our objective is to identify key communications and study their prevalence in online social interactions. Methods The American Diabetes Association Online community is an online social network for diabetes self-management. We analyzed 80,481 randomly selected deidentified peer-to-peer messages from 1212 members, posted between June 1, 2012, and May 30, 2019. Our mixed methods approach comprised qualitative coding and automated text analysis to identify, visualize, and analyze content-specific communication patterns underlying diabetes self-management. Results Qualitative analysis revealed that “social support” was the most prevalent theme (84.9%), followed by “readiness to change” (18.8%), “teachable moments” (14.7%), “pharmacotherapy” (13.7%), and “progress” (13.3%). The support vector machine classifier resulted in reasonable accuracy with a recall of 0.76 and precision 0.78 and allowed us to extend our thematic codes to the entire data set. Conclusions Modeling health-related communication through high throughput methods can enable the identification of specific content related to sustainable chronic disease management, which facilitates targeted health promotion.

BACKGROUND Online communities have been gaining popularity as support venues for chronic disease management. User engagement, information exposure, and social influence mechanisms can play a significant role in the utility of these platforms. OBJECTIVE In this paper, we characterize peer interactions in an online community for chronic disease management. Our objective is to identify key communications and study their prevalence in online social interactions. METHODS The American Diabetes Association Online community is an online social network for diabetes self-management. We analyzed 80,481 randomly selected deidentified peer-to-peer messages from 1212 members, posted between June 1, 2012, and May 30, 2019. Our mixed methods approach comprised qualitative coding and automated text analysis to identify, visualize, and analyze content-specific communication patterns underlying diabetes self-management. RESULTS Qualitative analysis revealed that “social support” was the most prevalent theme (84.9%), followed by “readiness to change” (18.8%), “teachable moments” (14.7%), “pharmacotherapy” (13.7%), and “progress” (13.3%). The support vector machine classifier resulted in reasonable accuracy with a recall of 0.76 and precision 0.78 and allowed us to extend our thematic codes to the entire data set. CONCLUSIONS Modeling health-related communication through high throughput methods can enable the identification of specific content related to sustainable chronic disease management, which facilitates targeted health promotion.

Cheating detection models in the online games can be divided in to two parts. The one is on client based model, which is designed to detect malicious programs not to be run while playi ng the games. The other one is server based model, which distinguishes the difference between benign users and cheaters by the server log analysis. The client based model provides various features to prevent games from cheating, For instance, Anti-reversing, memory manipulation and so on. However, being deployed and operated on the client side is a huge weak point a s cheaters can analyze and bypass the detection features. That Is why the server based model is an emerging way to detect chea ting users in online games. But the simple log data such as FPS’s one can be hard to find validate difference between two o f them. In this paper, In order to compensate for the disadvantages of the two detection model above, We use the existing game security solution log as well as the server one to bring high performance as well as detection ratio compared to t he existing detection models in the market.Keywords: Online game security solution, FPS Online game security, FPS S erver log analysis

Background Diabetes and Alzheimer disease and related dementias (ADRD) are the seventh and sixth leading causes of death in the United States, respectively, and they coexist in many older adults. Caring for a loved one with both ADRD and diabetes is challenging and burdensome. Objective This study aims to explore diabetes-related topics in the Alzheimer’s Association ALZConnected caregiver forum by family caregivers of persons living with ADRD. Methods User posts on the Alzheimer’s Association ALZConnected caregiver forum were extracted. A total of 528 posts related to diabetes were included in the analysis. Of the users who generated the 528 posts, approximately 96.1% (275/286) were relatives of the care recipient with ADRD (eg, child, grandchild, spouse, sibling, or unspecified relative). Two researchers analyzed the data independently using thematic analysis. Any divergence was discussed among the research team, and an agreement was reached with a senior researcher’s input as deemed necessary. Results Thematic analysis revealed 7 key themes. The results showed that comorbidities of ADRD were common topics of discussions among family caregivers. Diabetes management in ADRD challenged family caregivers. Family caregivers might neglect their own health care because of the caring burden, and they reported poor health outcomes and reduced quality of life. The online forum provided a platform for family caregivers to seek support in their attempts to learn more about how to manage the ADRD of their care recipients and seek support for managing their own lives as caregivers. Conclusions The ALZConnected forum provided a platform for caregivers to seek informational and emotional support for caring for persons living with ADRD and diabetes. The overwhelming burdens with these two health conditions were apparent for both caregivers and care recipients based on discussions from the online forum. Studies are urgently needed to provide practical guidelines and interventions for diabetes management in individuals with diabetes and ADRD. Future studies to explore delivering diabetes management interventions through online communities in caregivers and their care recipients with ADRD and diabetes are warranted.