Text Analysis and Topic Models: An Introduction for Social Scientists

Introductory workshop in R to text analysis and topic models for graduate students in social sciences. January 10, II Chilean Social Network Conference CHISOCNET, UC Chile.

Text Analysis and Mining (TAM)

One of the most dynamic areas in the development of new analytical tools in computational social science is text analysis and mining (TAM). This field leverages computational tools and methods to systematically process and examine textual data.

In general terms, TAM:

• From a computational perspective, TAM employs methods and algorithms to process, interpret, and extract meaningful information from textual sources.
• It integrates techniques from natural language processing (NLP), data mining, and machine learning to analyze unstructured data—such as text represented as sequences of words.
• It facilitates the identification of patterns, relationships, and trends across large text corpora, including news articles, social media posts, and academic documents.
• It serves as an efficient and scalable tool, capable of managing large volumes of data through automated processing.

Fig: TAM Families.

Registration

To register for this workshop, please subscribe to the II Chilean Social Network Conference (CHISOCNET), hosted by UC Chile, via the following link:
CHISOCNET Conference, 2025