17 August 2018
Theorizing and Analyzing Social Media in Political Communication and Journalism
Social media (such as Twitter, Facebook, YouTube, WhatsApp, Plurk, Renren) are important new digital platforms for online social networking and microblogging to discuss all kinds of issues (serious and trivial). Basically, whatever keeps people busy. This kind of public communication has received a lot of positive, but mainly negative attention in the mainstream media as well as in the social sciences.
A subdivision of social media research concerns how regular people (citizens), political actors (politicians, organizations) and media professionals (journalists) use social media to share opinions about issues, create online communities and to inform or to win people over; e.g. to vote for them. In this course you will learn how to look at these social media data to understand how journalists, politicians, and citizens use social media.
The course has three main parts: (a) theorizing social media, (b) theorizing online journalism and political communication, and (c) methods of data collection and analysis of social media.
Theorizing social media will look at specifics of social media design and how this affects online communication and networks. This theme is generic to all kinds of social media and connected digital media. Subsequently we will look at theorizing social media in journalism and political communication uses traditional an new approaches to theorize social media such as agenda setting research, networked journalism.
Furthermore we will discuss and use methods of collection and analysing social media data. This empirical and hands-on part will focus on understanding the structure of social media data (e.g. networks based on social connections, but also sharing activities), the dynamics of social media data (e.g. change across time of social media activity), the actual content of social media (i.e. expressed opinions).
The programme of the first week will focus on theory, although methods are included in those sessions. The second week we will have interactive seminars on how to collect social media data, how to develop measurements instruments, and analysing social media in terms of structure anci content. We will use R as our tool for data collection, and data analysis.
Advanced Bachelor, Master, PhD, Postdoc, Professional. This social media course is for the curious at heart, specifically regarding online social relations and online communication on social media. Even though there are many complaints about social media, being addictive, polarizing, and invested with Fake News, we as academics still have a lot of ground to cover to understand the role of social media in news; political campaigns, media hypes.
At the same time, social media communication can turn out to be quite complex (d. networked communication). Due to this complexity, students, who want to apply, have a broad interest in social and communication processes.
Students who like the in-depth analysis of online social behaviour and online content, and do not eschew the occasional mathematical formula, this course is for you.
After this course you are able to:
1. Theorize how journalists and politicians use social media
There are several theoretical approaches to understanding social media use in general, but also specifically in the fields of political communication and journalism. How to apply theories and hypotheses to data in these two field will be the focus the first week.
2. Understand the different methods needed to test theories on social media in political communication and journalism. Specific theories and hypotheses require specific research designs, methods and
3. In week two the focus will be on Rasa data collection technique, as well as an analytical tool for testing hypotheses. You will be able to access Application Programming Interfaces (APis), in order to access data. You will be able to set up an R installation on your computer, and find and install relevant packages.
4. You will be able to perform basic analyses on social media data using R This will range from frequencies, cross tabulation, correlations, multidimensional scaling and regression analysis. The data that will be used will mostly be provided for, but also data collected during the course will be used.
EUR 985: The fee includes the registration fees, course materials, access to library and IT facilities, coffee/tea, lunch, and a number of social activities.
We offer several reduced fees:
€ 887 early bird discount – deadline 1 April 2018 (10%)
€ 837 partner and RU discount (15%)
€ 739 early bird + partner and RU discount (25%)