Victoria Meil, Chair of Quantitative Marketing and Consumer Analytics: Social Media Data (April 2023)

Victoria Meil acquired both her Bachelor's and Master's degrees in Business Administration with a focus on Marketing, Human Resources and Psychology at the University of Mannheim. She spent a semester abroad at Queen's University in Canada. During her studies, Victoria gained practical experience in online marketing, content marketing and HR at well-known, international companies.

Since September 2021, Victoria is a doctoral candidate at the Chair of Quantitative Marketing and Consumer Analytics (Prof. Florian Stahl). As such, she follows the Marketing Track of the structured PhD program administered by the Center of Doctoral Studies in Business at the University of Mannheim. Her research interests are primarily in consumer psychology, social marketing, machine learning in marketing, and employer branding.

What is your current research topic?

I'm currently working on two very different topics in social media: Influencer Marketing and Online-Offline Spillover Effects. In the area of influencer marketing, I'm looking at influencer marketing for social projects and NPOs, together with Florian Stahl and Maximilian Beichert. We also analyze the storytelling of influencers and the effects on sales and engagement. In the area of online-offline spillover effects, I work together with Florian Stahl, Jacob Goldenberg and Isabella Hartig, and we look at how online identity affects offline behavior.

For those who have not yet delved deeply into the topic of Data Science: How would you explain to a child what you are working on?

Imagine that someone you like posts many photos and videos of himself/herself on social networks. This person has many people watching and listening to him/her, so this person is called an “influencer”. Sometimes this Influencer sells things that he/she uses and likes, such as clothes or jewelry. But sometimes the influencer also uses his/her reach to promote good things, like projects that help other people. We call this influencer marketing for social projects and NPOs. I'm also looking at how the stories influencers tell can make us buy or support certain things.
Another topic I work on has to do with identity. Sometimes we show a different side of ourselves online than we do offline. I want to find out if what we do and say online affects us offline (in real life). For example, whether we are actually motivated to do more sports after watching a lot of sports online.

Everyone talks about Data Science – how would you describe the importance of the topic for yourself in three words?

Insightful, coding, analytical

What points of contact with Data Science does your work have? Which methods do you already use, and which would be interesting for you in the future?

We are still very much at the beginning with both topics. However, we use both Python for preprocessing and R for the statistical models. The methods then depend on the project and the respective data and questions. In the area of computer vision and text processing, we mainly use neural networks. For a first data exploration it can also be simpler and faster methods, like dictionary-based topic modeling in speech processing or image analysis methods.

How high is the value of Data Science for your work? Would your research even be possible without Data Science?

Data science is essential for my projects. Without modern data science, the data volumes would not really be manageable and we would not be able to gain the insights from the data with which we conduct research.

What development opportunities do you see for the topic of Data Science in relation to your field?

Particularly in social media, some data is very easy to obtain, while other data, such as Stories on Instagram, is still partly a black box. I would like to see the data protection regulations and options become even more research friendly. In addition, it would be nice if Open Science became even bigger.

Back