About Us

The Textual Analytics & Publications Lab (TAPLab) is dedicated to advancing the use of text data for strategic insights in various business contexts. Prioritizing both text data capture and research publications alongside robust analytics, the lab not only transforms unstructured data into actionable insights but also contributes to the broader academic and professional community through cutting-edge research. By providing tailored analytics frameworks, the lab enables companies to draw meaningful conclusions from customer reviews, social media, and internal communications, supporting data-driven decisions that enhance market positioning and customer engagement.

One of the TAPLab’s activities is applying sentiment analysis to text datasets—an essential tool for understanding emotions and communicative perspectives. Using advanced natural language processing (NLP) and machine learning algorithms, the lab can detect nuanced tones in large textual datasets such as online feedback, allowing researchers to gauge public sentiment toward strategic assets such as brands, campaigns, products, and services with precision. By interpreting emotional cues and shifts in sentiment over time, companies can make informed improvements, increase customer satisfaction, and foster brand loyalty.

In addition to sentiment analysis, TAPLab specializes in advanced cluster analysis to uncover patterns and create thematic understanding based upon large text datasets. These clustering techniques reveal valuable insights into distinct human symbolic understanding and emerging text-based trends, allowing organizations to tailor strategies for specific audiences. For instance, identifying shared characteristics within text clusters allows businesses to design marketing campaigns, product features, and customer service initiatives that resonate with unique customer segment.

Beyond analytics, TAPLab is committed to text data capture—ensuring reliable, comprehensive data collection from a variety of sources. By using sophisticated data extraction and filtering methods, the lab creates datasets that serve as foundation for accurate analysis. This data capture process is crucial for deriving insights that reflect genuine customer behavior and industry trends, enabling businesses to respond to real-time developments.

Lastly, TAPLab places a strong emphasis on publishing research that contributes to the evolving field of text analytics. Through academic and industry-focused publications, the lab shares its findings and methodologies with a wider audience, fostering innovation and thought leadership in applied text analysis. By engaging in research dissemination, the lab both solidifies its expertise and advances best practices, shaping how businesses across industries can leverage text analytics for competitive advantage.

Both in and out of the classroom, students have had the opportunity to work on various projects in the lab. Data sets and projects they've completed so far include:

• Finding sentiment and thematic analysis for 2023-24 job data for Evansville, Indianapolis, Louisville, Nashville, St. Louis and others.
• Online Forum and Social Post discussion of Blockchain, Generative AI, XR/VR/AR, Virtual Humans and more.
• Analyzing discussion about the 2024 Solar Eclipse and what the most common themes, topics, etc. pertaining to the event included.

Bacic, D., Gilstrap, Cr., and Gilstrap, Cu. (2024). Understanding the Adoption of Generative Artificial Intelligence within Communities of Practice: A Cross-Practice, Machine Learning-Based Lexical Study. 2024 47th MIPRO ICT and Electronics Convention (MIPRO). 

Bacic, D., Gilstrap, Cr., Gilstrap, Cu., McKnight, M., Shemroske, K. and Srivastava, S. (2024). Generative Artificial Intelligence in Applied Business Contexts: A Systematic Review, Lexical Analysis, and Research Framework. In: Journal of Applied Business and Economics. 

Gilstrap, Cr., Gilstrap, Cu. and Weber, T. (2024). Navigating The Unknown: How Healthcare Entrepreneurs Manage Uncertainty. In: Journal of Developmental Entrepreneurship. 

Gilstrap, Cr. and Gilstrap, Cu. (2023). Mobile Technologies and Live Streaming Commerce: A Systematic Review and Lexical Analysis. 2023 46th MIPRO ICT and Electronics Convention (MIPRO). 

Gilstrap, Cu. and Park, S. (2022). The language of social media contests: A lexical analysis of contests across social platforms. In: Journal of Digital & Social Media Marketing.