Join the SMRConverge google group to discuss this week’s discussion topic: How should we approach social media data knowing that different sub-groups use platforms in different ways?
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Academic Research
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Analysis of Popular Social Media Topics Regarding Plastic Pollution. Phoey Lee Teh, Scott Piao, Mansour Almansour, Huey Fang Ong and Abdul Ahad. Sustainability. [Environmental Science].
Detecting country of residence from social media data: a comparison of methods. V. Heikinheimo, O. Järv, H. Tenkanen, T. Hiippala and T. Toivonen. International Journal of Geographical Information Science. [GIScience]..
Cross-platform- and subgroup-differences in the well-being effects of Twitter, Instagram, and Facebook in the United States. Kokil Jaidka. Nature Scientific Reports. [Human Behavior].
Science Factionalism: How Group Identity Language Affects Public Engagement With Misinformation and Debunking Narratives on a Popular Q&A Platform in China. Kaiping Chen, Yepeng Jin, and Anqi Shao. Social Media + Society. [Computational Social Science].
DEA-RNN: A Hybrid Deep Learning Approach for Cyberbullying Detection in Twitter Social Media Platform. Belal Abdullah Hezam Murshed, Jemal Abawajy, Suresha Mallappa, Mufeed Ahmed Naji Saif, and Hasib Daowd Esmail Al-ariki. IEEE Access. [Computer Science].
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Calls for Papers
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“7th International Workshop On Social Sensing: Special Edition On Information Operation On Social Media.” ICWSM. Papers Due: March 27, 2022. Historically, the intent of the social sensing workshop has been to combine scientists from computing, social, and cognitive domains around social media-related topics. With belief dynamics (and their relation to information/influence operations) as the topic in 2022, we invite papers and vision abstracts that approach it from different perspectives, from physical signal processing to social science and from control to cognitive modeling.
“Pervasive Health: Social Media Analytics and Sensing for Healthcare and well-being”. Social Network Analysis and Mining. Submissions Due: March 31, 2022. The special issue solicits empirical, experimental, methodological, and theoretical research reporting original and unpublished results on social media analysis and mining on topics in the realm of healthcare and health informatics along with applications to real-life situations.
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML PKDD. Abstracts Due: March 30, 2022. In the Research track, we welcome research articles in all fields of machine learning, knowledge discovery, and data mining. In the Applied Data Science track, we seek articles that highlight unique applications of machine learning, data mining, and knowledge discovery to real-world problems, bridging the gap between practice and current theory.
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Calls for Proposals
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Pioneering Ideas: Exploring the Future to Build a Culture of Health. Robert Wood Johnson Foundation. Rolling Deadline. One focus of this grant is the ‘Future of Social Interaction. New technologies including social media are changing the nature of our individual and group social interactions. How these tools and platforms are designed now and in the future—and by whom—present both opportunities and challenges for reducing social isolation or promoting exclusivity; for fostering civil society or promoting divisiveness; for creating a more collaborative, inclusive workforce or promoting a more fractured and less empowered workforce.
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Events, Tutorials & Workshops
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The Social Media Summit. MIT Initiative for the Digital Economy. Thursday, March 31, 2022. The purpose of this event is to understand the impact of social media, revisit public policy frameworks that will best govern this impact, and craft an agenda going forward about how to achieve the promise of social media and avoid its peril.
Responsible Data Science and AI mini-symposium. Michigan Institute for Data Science. Wednesday, April 6 - Thursday, April 7, 2022. This event, open to the public, will feature several talks discussing the impact data science and AI have on society.
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We would like to thank the S3MC funders for supporting this newsletter, with special thanks to the McCourt School’s Massive Data Institute (MDI) at Georgetown University.
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