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FRG Informal Talk Series: Andrew Liu and Wan Zhang

November 16, 2023 @ 2:00 pm - 3:00 pm

2:00-2:15pm Lighting talk by Andrew Liu

Title: Public Perceptions of Synthetic Cooling Agents on Twitter

Abstract: Amid a potential menthol ban, electronic cigarette (e-cigarette) companies are incorporating synthetic cooling agents like WS-3 and WS-23 to replicate menthol/mint sensations. This study examines public views on synthetic cooling agents in e-cigarettes via Twitter data. From May 2021 to March 2023, we used Twitter Streaming API, to collect tweets related to synthetic cooling agents with keywords such as ‘WS-23,’ ’ice,’ and ’frozen.’ Two deep learning roBERTa models, classified attitudes expressed in tweets about synthetic cooling agents and identified e-cigarette users. The BERTopic deep-learning model identified major topics of positive and negative tweets. Two proportion Z-tests were used to compare the proportions of positive and negative attitudes between e-cigarette users (vapers) and non-e-cigarette-users (non-vapers). Of 6,940,065 e-cigarettes related tweets, 5,788 non-commercial tweets related to synthetic cooling agents. The longitudinal trend analysis showed a clear upwards trend in discussions. Vapers posted most of the tweets (73.05%, 4,228/5,788). Nearly half (47.87%, 2,771/5,788) held a positive attitude toward synthetic cooling agents, which is significantly higher than those with a negative attitude (19.92%,1,153/5,788) with a P-value < 0.0001. The likelihood of Vapers expressing positive attitudes (60.17%, 2,544/4,228) was significantly higher (P < 0.0001) than that from non-vapers (14.55%, 227/1,560). Conversely, negative attitudes from non-vapers (30%, 468/1,560) was significantly (P < 0.0001) higher than vapers (16.2%, 685/4,228). Prevalent topics from positive tweets included “enjoyment of specific vape flavors,” “preference for lush ice vapes,” and “liking of minty/icy feelings.” Major topics from negative tweets included “disliking certain vape flavors” and “dislike of others vaping around them.” On Twitter, vapers are more likely to have a positive attitude toward synthetic cooling agents than non-vapers. Our study provides important insights into how the public perceives synthetic cooling agents in e-cigarettes, insights that are crucial for shaping future FDA regulations aimed at safeguarding public health.


2:15-2:50pm Informal talk by Wan Zhang

Title: Regularization of BELIEF under Smoothness Interpretations

Abstract: The binary expansion linear effect (BELIEF) is an alternative framework to the popular GLM framework by taking advantage of a parallelism between bi-variate binary distributions and bi-variate normal distributions. One major challenge in the BELIEF framework is the exponential growth in dimensionality. To ensure statistical estimation and computational scalability, we propose a novel definition of smoothness for binary interactions. We have proved that this correspondence between the smoothness of each marginal binary interaction and the interaction itself is a one-to-one function. Additionally, we have shown that in higher dimensions, the smoothness of a binary interaction can be expressed as a product of marginal binary interactions. Based on these observations, we propose to model the dependency that is smooth with a generalized LASSO model with larger penalty on less smooth terms. The numerical studies show that the smooth LASSO for BELIEF provides several key advantages in interpretability and effectiveness.


November 16, 2023
2:00 pm - 3:00 pm

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