Data Skeptic

Chances are that you have bought a product online majorly because of the reviews you saw. Unfortunately, not all reviews are genuine. Today, Rajvardhan Oak shares some insight from his research on fraudulent Amazon reviews. He explained the inner workings of fraudulent reviews and revealed key insights from his qualitative and quantitative study.

While we give attention to textual data on the web, many do not know the unique power of echo interactions with smart devices for ad targeting. Today, our guest, Umar Iqbal joins us to discuss his study on using Amazon Smart Speakers for ad targeting. He gave interesting revelations about how voice data is captured and analysed for ad purposes. Listen to find out more.

Rajan Udwani, an Assistant Professor at the University of California Berkeley joins us to discuss his work on AdWords with unknown budgets. He discussed the previous approaches to ad allocation, as well as his maiden approach that introduced randomization for better results. Listen for more.

Today, we are joined by Piotr Niedźwiedź, Founder and CEO of Neptune.ai. Piotr discusses common MLOps activities by data science teams and how they can take advantage of Neptune.ai for better experiment tracking and efficiency. Listen for more!

Affiliate marketing creates an opportunity for marketers to gain a commission by promoting a product or service.  Cookies are typically used for tracking and the advertiser whose product or service is being featured pays the marketing only on transactions. Today's episode covers those approaches and is also a story of conflict between two large companies and how one affiliate marketer got caught in the middle.

Cameron Ballard joins us today to discuss his work around YouTube conspiracy theories. He revealed interesting observations about conspiracy theories on YouTube including how predatory ads are most common in conspiracy theory videos and how YouTube’s algorithm subtly works for predatory ads. 

Eric Zeng joins us to discuss his study around understanding bad ads and efforts that can be taken to limit bad ads online. He discussed how he and his co authors scrapped a large amount of ad data, applied a machine learning algorithm, and commensurate statistical results.

NaLette Brodnax, a political scientist and an Assistant Professor in the McCourt School of Public Policy at Georgetown University joins us to discuss her work on analyzing digital advertisements for political campaigns. She used data for electoral campaigns on Facebook to answer questions that help us better understand how digital ads affect the outcome of elections.   Click here for additional show notes! Thanks to our sponsor! https://neptune.ai/ Log, store, query, display, organize and compare all your model metadata in a single place