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Blog 6: Collecting the corpus and preparing the lexical analysis

2021-12-22

French

Research Notebook

'Mixology' is an open research project, which aims to extract opinions in times of crisis, here from a corpus collected via the Twitter API, from December 12 to 31, 2021.

The collection of the corpus has been going on for nine days. At this stage, the four queries axes have given rise to:

The preparation of the lexical analysis has started, in English, based on the « vaccination » corpus. The R packages used are: tm, tidytext, wordcloud

It has required significant data cleansing, which is still ongoing.

However, this activity made it possible to identify the first set of the most frequently used terms by the nearly 50,000 unique users and a list of stop words adapted to the corpus (according to the fitness for use principle). These first versions are available on Github: https://github.com/laurence001/mixology

This preparation also made it possible to identify a polarization of opinions at least around four topics related to the “vaccination” corpus: health (pro-vaccines, anti-vaccines, anti-mRNA vaccines, role of big pharma), information (facts and disinformation), political measures (adhesion and resistance with a vocabulary sometimes borrowed from the darkest moments of history to highlight a form of authoritarianism, pro, and anti-obligation vaccine). In all three cases, the question of trust is already emerging. These findings will need to be confirmed during the actual analysis phase, which will also consider the French language.

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Read more

Blog 21: Politicians, experts, and journalists

Blog 20: For vaccination, against restrictions

Blog 19: Comparative Sentiment Analysis

Blog18: A health and political crisis

Blog 17: Anatomy of the “political/sanitary measures” sub-corpus (en)

Blog 16: Sentiment analysis of the ‘vaccination’ sub-corpus (en, part.2)

Blog 15: Comparative sentiment analysis of the ‘vaccination’ sub-corpus (en, part.1)

Blog 14: An adapted dictionary for the Covid crisis and sentiment analysis

Blog 13: Building a stop words list

Blog 12: Main Dictionaries for Sentiment Analysis

Blog 11: Statistical description of the corpus #RStats

Blog 10: Sentiment analysis or the assessment of subjectivity

Blog 9: Topic modeling of the ‘vaccination’ corpus (English)

Blog 8: Linguistic and quantitative processing of the ‘vaccination’ corpus (English, part.2)

Blog 7: Linguistic and quantitative processing of the ‘vaccination’ corpus (English, part.1)

Blog 6: Collecting the corpus and preparing the lexical analysis

Blog 5: The textclean package

Blog 4: Refining the queries

Blog 3: The rtweet package

Blog 2: Collecting the corpus

Blog 1: An open research project

The challenges of research on media use in times of crisis