Home Institution
University of Notre Dame
Publication Date
Spring 2019
Abstract
Understanding how a migrant population is viewed and displayed by the host country has been a struggle for a long period of time for anyone studying migration. Traditional methods of collecting information were tedious, time intensive and expensive. However, Big data has been providing unique solutions to gaps in information in many different fields across the world. Media plays an important part in developing and assessing the public opinion on a topic. With the availability of a large number of online articles from historical time periods, it is possible to use quantitative analysis, such as text analytics, to can see how the ‘migrant’ is presented in local Dutch newspapers using online records of articles. Average sentiment of the analyzed articles were in general negative but also varied over time, with negative sentiment peaking in 2015 which is correlated with high unemployment in the country. Words most commonly associated with articles with keyword ‘migrant’ included ‘work’, ‘policy’ and ‘jobs’ suggesting that migrants are often portrayed in an economic or political context.
Disciplines
Categorical Data Analysis | Dutch Studies | Journalism Studies | Migration Studies | Models and Methods | Sociology of Culture
Recommended Citation
Schmitz, Nicholas J., "Newsworthy Migrants: Sentiment and Text Analysis of Dutch Newspapers" (2019). Independent Study Project (ISP) Collection. 3062.
https://digitalcollections.sit.edu/isp_collection/3062
Included in
Categorical Data Analysis Commons, Dutch Studies Commons, Journalism Studies Commons, Migration Studies Commons, Models and Methods Commons, Sociology of Culture Commons
Program Name
Morocco: Migration and Transnational Identity