Social Data Collaboratory

More about social media! I thought this comment, in reaction to the proposed warning labels, was super interesting: "Dr. Odgers said the nation’s top health official was running the risk of labeling normal adolescent behavior as “shameful, damaging and dangerous.” Missing in this conversation is the pervasiveness and effects of undisclosed influencer marketing of commercial determinants of health--e.g., tobacco, alcohol, cannabis, prescription drugs, online gambling.

📢New research alert! At NORC at the University of Chicago's Social Data Collaboratory (SDC), we examined the efficacy of influential account metrics for social media studies, shedding light on crucial tools needed by public health and public opinion researchers to identify influential accounts. Key Takeaways: 📊Effective Metrics: We identified distinct metrics for measuring influential accounts on social media, crucial for understanding discussions around topics. 🌐Metric Diversity: Using a variety of metrics is essential to accurately capture different types of influential accounts and their impact on public health conversations. 🕰️Tailored Research Approaches: Researchers should consider the temporal dimension and account types captured by different metrics to design more effective studies in public health and social media. These insights highlight the importance of leveraging diverse metrics to gain comprehensive insights into how social media influencers shape public health discussions. 📑Read the full study here: https://lnkd.in/dE_Qb4ff 🤝Interested in collaborating on research to address public health challenges in the digital age? Contact us to explore innovative solutions and partnerships! #SocialData #DigitalInsights #ResearchAnalytics #SocialTrends

We're beginning to see a trade-off between creating paywalls for training data access and letting the AI companies just extract value from others' content. I'm all for honoring copyrights and having the AI developers pay for the valuable resource. However, one of the most concerning (to me) consequences of protecting data provenance is that academics and not-for-profit researchers face yet another paywall for access to data. There's already a divide between those who can afford access to data and those who cannot. It's only going to get worse unless the US adopts a new approach to digital regulation that protects public and research use applications.

Short-video social media platforms like #TikTok and #Reels are experiencing a surge in popularity. At NORC at the University of Chicago's Social Data Collaboratory (SDC), we are proactively embracing video research methodologies to stay ahead. Haoyu Shi has recently leveled up our capabilities by attending Video Research Institute at Purdue University, expanding our expertise from traditional text analyses to cutting-edge audio and video technologies. What's New? We're now equipped with advanced tools for: 🗣️ Vocal Pitch Analysis for Emotion 🔊 Wav2Vec Audio Embeddings 🫰 Gesture & Facial Expression Detection 🐇 Obejct Detection & Motion Tracking 🌐 Multimodal Deep Learning Join us in exploring the limitless possibilities of video research. Your insights could shape the future of how we interact with media! 🔗 Stay Connected, Stay Informed. #VideoResearch #Innovation #AI #MachineLearning #ResearchExcellence #Multimodal #DeepLearning #SocialMedia

It's so much easier to propagate disinformation than to correct or neutralize it because 'truth' is rarely categorical and is often interpreted through cultural context. It's fascinating that the misinformation machines can so easily identify those appeals, the two truths, that contextualize and make plausible the one lie. The challenge for researchers is to a) recognize the complexity, and b) to honor, rather than dismiss, the context that makes the disinformation salient. Only when we can do that, and do it at scale and with speed, will we be able to achieve progress. No small challenge!

At the 2024 Justice Community Opioid Innovation Network (JCOIN) meeting, Alex Kresovich highlighted our team's groundbreaking work on opioid-related content on social media platforms like Facebook and Instagram. 🔍Our research offers pivotal insights into how these platforms influence public opinion and dialogue around the opioid crisis. Using CrowdTangle, we collected data from Facebook and Instagram posts related to the opioid epidemic in the US, spanning from July 1, 2022, to June 30, 2023. We focused on the top 0.5% of posts with the highest engagement, analyzing 1,267 key posts. Key Findings: 🚓 Law enforcement narratives dominated the conversation, with frequent mentions of fentanyl and heroin. 💔 Discussions on opioid treatments and harm reduction were notably sparse. ⚖️ Partisan differences were evident: right-leaning accounts blamed drug dealers and government policies, often using sensationalist language. 💬 Celebrity overdose news, though rare, generated high engagement. 📰 Local news posts focused heavily on criminality and police action, often mirroring police press releases. 📊 Our research reveals a shift towards a criminal justice lens in public discourse around the opioid crisis. Right-leaning narratives are more prevalent, with limited criticism of pharmaceutical companies or healthcare providers. The emphasis on celebrity overdoses and police narratives highlights significant societal influences on public perception. Opportunities Ahead: 💡Public health entities can leverage these insights to promote evidence-based information and foster constructive conversations. 🤝By collaborating with influential social media accounts and law enforcement, we can help reshape the narrative and tackle the opioid crisis more effectively. #OpioidCrisis #PublicHealth #SocialMediaResearch #JCOIN2024 #EvidenceBasedPolicy #HealthCommunication

🎆Happy Fourth of July from NORC at the University of Chicago Social Data Collaboratory (SDC)!

Mining social media data is a huge opportunity for research—but there are clear risks for privacy and security. At NORC at the University of Chicago's Social Data Collaboratory (SDC), we're addressing the challenges and opportunities of mining social data for research and innovation. Key takeaways from our recent research: 1. Potential for Innovation💡: Social media data offers valuable insights for diverse fields, but transparency and standards are lacking. 2. Risk of Data Misuse⚠️: Without clear procedural standards, there's a risk of bias and spurious findings in social media research. 3. Proposing Criteria for Quality📝: We propose clear evaluation criteria and documentation guidelines to ensure transparency and credibility in research studies using social media data. We aim to establish clear standards for collecting, analyzing, and reporting social data. Let's collaborate to advance responsible social media research and drive impactful decisions. Read more about our research here: https://lnkd.in/e_qkpmvT #SocialDataResearch #TransparencyInResearch

Happy Juneteenth! Do you know the story of #Juneteenth? Learn more here @NMAAHC: nmaahc.si.edu/Juneteenth.

What type of analyses can the SDC do? One of our many innovative methods here at NORC at the University of Chicago’s Social Data Collaboratory (SDC) is to harness the power of advanced techniques like supervised and unsupervised machine learning to analyze social media data in innovative ways. 🔍 Supervised Learning: Think of this as "guided learning." We use labeled data to train algorithms to make predictions or classifications. For example, we can teach machines to identify sentiment in social media posts—positive, negative, or neutral. 🧠 Unsupervised Learning: Here, algorithms explore data on their own to find patterns and relationships without predefined outcomes. It's like discovering hidden connections in a vast sea of information. We apply this to uncover emerging trends or topics in social media conversations. At the SDC, we decode the complexities of social media data to provide actionable insights for diverse industries—from public health to marketing. Our approach empowers organizations to make informed decisions and drive impactful strategies. Ready to leverage the potential of social data with machine learning? Contact us today to explore how the SDC can support your research and analytical needs. Let's navigate the world of social data together! https://lnkd.in/eY5tdMFF 🌐 #SocialData #MachineLearning