Data Skeptic27 Nov 2020

Face Mask Sentiment Analysis

As the COVID-19 pandemic continues, the public (or at least those with Twitter accounts) are sharing their personal opinions about mask-wearing via Twitter. What does this data tell us about public opinion? How does it vary by demographic? What, if anything, can make people change their minds?

Today we speak to, Neil Yeung and Jonathan Lai, Undergraduate students in the Department of Computer Science at the University of Rochester, and Professor of Computer Science, Jiebo-Luoto to discuss their recent paper. Face Off: Polarized Public Opinions on Personal Face Mask Usage during the COVID-19 Pandemic.

Works Mentioned
https://arxiv.org/abs/2011.00336

Emails:
Neil Yeung
nyeung@u.rochester.edu

Jonathan Lia
jlai11@u.rochester.edu

Jiebo Luo
jluo@cs.rochester.edu

Thanks to our sponsors!

Springboard School of Data offers a comprehensive career program encompassing data science, analytics, engineering, and Machine Learning. All courses are online and tailored to fit the lifestyle of working professionals. Up to 20 Data Skeptic listeners will receive $500 scholarships. Apply today at springboard.com/datasketpic
Check out Brilliant's group theory course to learn about object-oriented design! Brilliant is great for learning something new or to get an easy-to-look-at review of something you already know. Check them out a Brilliant.org/dataskeptic to get 20% off of a year of Brilliant Premium!

Denne episoden er hentet fra en åpen RSS-feed og er ikke publisert av Podme. Den kan derfor inneholde annonser.

Episoder(601)

MS Connect Conference

Cloud services are now ubiquitous in data science and more broadly in technology as well. This week, I speak to Mark Souza, Tobias Ternström, and Corey Sanders about various aspects of data at scale. ...

9 Des 201642min

Causal Impact

Today's episode is all about Causal Impact, a technique for estimating the impact of a particular event on a time series. We talk to William Martin about his research into the impact releases have on ...

2 Des 201634min

[MINI] The Bootstrap

The Bootstrap is a method of resampling a dataset to possibly refine it's accuracy and produce useful metrics on the result. The bootstrap is a useful statistical technique and is leveraged in Bagging...

25 Nov 201610min

[MINI] Gini Coefficients

The Gini Coefficient (as it relates to decision trees) is one approach to determining the optimal decision to introduce which splits your dataset as part of a decision tree. To pick the right feature ...

18 Nov 201615min

Unstructured Data for Finance

Financial analysis techniques for studying numeric, well structured data are very mature. While using unstructured data in finance is not necessarily a new idea, the area is still very greenfield. On ...

11 Nov 201633min

[MINI] AdaBoost

AdaBoost is a canonical example of the class of AnyBoost algorithms that create ensembles of weak learners. We discuss how a complex problem like predicting restaurant failure (which is surely caused ...

4 Nov 201610min

Stealing Models from the Cloud

Platform as a service is a growing trend in data science where services like fraud analysis and face detection can be provided via APIs. Such services turn the actual model into a black box to the con...

28 Okt 201637min

[MINI] Calculating Feature Importance

For machine learning models created with the random forest algorithm, there is no obvious diagnostic to inform you which features are more important in the output of the model. Some straightforward bu...

21 Okt 201613min