Contents of this section
5 pages
Analysis with Generative AI Recent advances in artificial intelligence have opened up new possibilities for text analysis through generative models such as ChatGPT or Gemini. These models can not only synthesize and summarize textual data, but also explore themes, detect sentiment, and interpret trends in a more fluid and flexible way.
In this section, we explore how these tools can be used for text analysis.
Ethics This module addresses the ethical issues involved in collecting, processing, and analyzing digital data. It is especially important when working with data drawn from online platforms, social networks, or user-generated content.
Objectives By the end of this module, you should be able to:
Identify the main ethical risks related to digital data collection. Better understand consent, privacy, and responsible reuse of data. Integrate ethical reflection into research and training practices. Ethics is not an optional add-on to digital methods. It is a central part of responsible data work.
Introduction Welcome to the first module in this series on data scraping without coding. This module focuses on extracting data from web platforms and social media using simple graphical tools, without requiring you to write a single line of code.
Objectives By the end, you will be able to:
Understand the basic concepts of data scraping. Identify data sources available online, such as social networks and websites. Use graphical tools to scrape data from those sources. Structure This module is organized into several sections:
Network Analysis This module introduces the main concepts and tools used to analyze social networks from digital data. It focuses on helping learners understand relationships between actors, interactions, and structures that emerge from online activity.
Objectives By the end of this module, you should be able to:
Understand the main concepts of network analysis. Identify tools used to visualize and interpret networks. Explore examples based on platforms such as Twitter and YouTube. Structure This module is organized into several sections:
Text Analysis This module introduces several approaches to text analysis, especially for textual data collected online. It is designed for people who want to move beyond data collection and begin exploring meaning, themes, tone, and patterns within a corpus.
Objectives By the end of this module, you should be able to:
Understand the main stages of text analysis. Identify tools that allow text analysis without heavy coding. Explore common methods such as sentiment analysis, topic modeling, and word enrichment. Structure This module is divided into several sections: