MethodsNet + RSS
MethodsNet + RSS

Big Data: Introduction to Text Analysis (RSS2.07) - Confirmed

In this course you delve into quantitative text analysis methods for social and political inquiries. You will learn to process, analyze, and derive insights from vast text datasets, including legislative speeches and social media posts. From basic approaches to advanced techniques like machine learning and topic models, you will master the tools to answer pressing social and political questions.

Duration: one-week.



    The application deadline has passed, applying is no longer possible

    Over the last two decades, social research has witnessed an unprecedented surge in accessible textual data, propelled by the remarkable advancements in computational methods. From extensive records of century-old legislative speeches to the colossal volume of social media content reaching hundreds of millions, textual data has become intrinsic to contemporary social science research. Understanding and effectively harnessing this data has never been more crucial.

    This concise yet comprehensive course is designed to equip you with the statistical expertise needed to navigate and extract insights from textual data of varying sizes. From collection and preprocessing to detailed analysis, you will gain familiarity with prevalent quantitative text analysis techniques, learning to discern and implement suitable methods for their research challenges. 

    The course begins with foundational aspects, including document processing and description, progressing to advanced methodologies like sentiment analysis, scaling techniques, supervised machine learning, and topic models. At the end, you will be familiar with contemporary quantitative text analysis methodologies, gaining expertise to select and apply suitable techniques to address your specific data and research problems effectively.


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    Starting date

    24 June 2024, 9 am
    Educational method
    Main Language
    24 June 2024, 9 am - 28 June 2024, 5 pm
    Bruno Castanho Silva
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    Radboud Summer School

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    Bruno Castanho Silva

    Bruno Castanho Silva

    Bruno Castanho Silva is an assistant professor for Methods in Empirical Social Research at the Freie Universität Berlin. He has a PhD in Political Science from the Central European University in Budapest, and was previously at the University of Cologne. He has taught multiple advanced methods courses, including text analysis and machine learning, in several countries. His work has appeared in the American Political Science Review, American Journal of Political Science, Journal of Politics, Political Analysis, and others.

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    • Regular: €1049 (application deadline 13th of May)
    • Student & PhD's: €699 (application deadline 13th of May)

    Includes: your course, short morning and late afternoon courses, coffee and tea during breaks, a warm lunch every day, Official Opening, MethodsNET Café (including some drinks and snacks) Official Closing (with some drinks and snacks) and a 1-year (2024 calendar year) free membership as MethodsNET regular member.

    Excludes: transport, accommodation, social events and other costs. 

    Discounts and Scholarships


    Level of participant: 

    • Master
    • PhD

    Admission requirements: 

    Participants should have basic familiarity with the R programming language. They should know how to open and manipulate data.

    Admission documents: