Isabella Kroon

Media Analysis: Chinese Investments in Africa

June 2023


China has made many investments in Africa, especially for the development of railways as part of its Belt and Road initiative. This project aims to understand how media outlets are covering these investments, including the topics they cover (ex. the environment, perspective of politicians, impact on economy) and whether that coverage is positive, negative, or neutral.

First, I created a program in Python to scrape news articles to collect the article's title, media source, date, text, and keywords and to write this data into a CSV file. I was provided with keyword dictionaries, which I applied to each text to understand what topics each article was covering. Finally, I used sentiment dictionaries to provide sentiment scores to the articles and their titles. Next, I created vizualizations of the data to answer the following questions:

  1. What proportion of articles each month were discussing a given topic? (Ex. African stakeholders)

    A graphed trend line, the graph is titled African stakeholders percentage per month

  2. What was the sentiment of articles covering a given topic? (Where 0 is neutral, 1 is positive, -1 is negative)

    A graphed trend line showing the sentiment scores of African stakeholder article titles

  3. Using unsupervised machine learning, what topics were frequently mentioned together?

    Topic models, a series of bar graphs showing words that commonly appear together

Reflections:
As the first research project I was a part of, I found this assignment very exciting. I had never done any kind of data scraping, but my problem-solving skills from previous computation classes allowed me to figure out how to solve any issues I came across. I was able to employ skills like dictionary analysis, machine learning techniques, and further develop my skills in R and Python. I am grateful to the DKU Summer Research Scholars program and to my professor for this opportunity!

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