Northwestern University

Jan
25
Wed 11:00 AM

Statistics Seminar Series: Generating Marketing Insights from Social Media Data

When: Wednesday, January 25, 2017
11:00 AM - 12:00 PM  

Where: 2006 Sheridan Road, B02, Evanston, IL 60208 map it

Audience: Faculty/Staff - Student - Post Docs/Docs - Graduate Students

Cost: Free

Contact: Kisa Kowal   847.491.3974

Group: Department of Statistics

Category: Academic

More Info

Description:

Title: Generating Marketing Insights from Social Media Data

Jennifer Cutler
Assistant Professor of Marketing, Northwestern University
Kellogg School of Management

Abstract:
Social media contain a wealth of information about consumers and market structures, and this has many marketers excited about the potential uses for such data. However, it is often not straightforward or cost-effective to process these data for reliable marketing insights. In particular, many approaches to commonly desired classification and prediction tasks (such as classifying text by topic or classifying users by demographics) rely on supervised learning methods, which require (often extensive) labelled training data. Such data can be difficult to obtain, and, due to the idiosyncratic and rapidly evolving user behavior on different platforms (e.g., “netspeak” slang), can become out-of-date quickly. In this talk, I will explore ways of leveraging the organic structure of social media data to circumvent the need for curated training data, resulting in unsupervised or distantly-supervised algorithms that are flexible, scalable, and highly automated. I will share examples of how such methods can be applied towards problems such as classifying marketer and user-generated text by topic, predicting demographic traits of users, and estimating the strength of brand image associations.

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