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Research Notebook

The 'Mixology' open research project aims to probe opinions in times of crisis from a corpus collected via the Twitter API. Its other objective is to develop an original research tool to be also reused for the analysis of headlines or media content (computational linguistics and machine learning methods), in line with media studies and journalism studies.

Blog 4: Refining the queries

14 décembre 2021

French

Several tests were necessary to calibrate the queries, which seem to perform poorly when a # is used. A watch of the trends posted on Twitter also led to the addition of the keywords ARN and mRNA, since the corpus analysis will be carried out in French and English.

Each retrieved dataset is first cleaned with Open Refine: column mergers are sometimes necessary because the “text” column is sometimes split into several columns (recording with comma separator). The three corpora with a defined geographical area present fewer quality problems than the general corpus, which targets all directions: big data does not necessarily mean good data.

Academic readings:

# # #

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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