News engagement under threat on Facebook?

Earlier this year, Mark Zuckerberg announced that the Facebook news feed would put more emphasis on social relations and less on news. This is the result of several controversies involving Facebook, especially the publication of fake news during the 2016 US elections. One of the concerns of news organizations is that changes to the algorithm may threaten their reach and the audience’s news engagement.

Having collected all posts by news organizations (n=356,188 from 59 Dutch news titles), I am able to analyze how much engagement these posts had and how this may have changed over time. I will look at the number of likes for each post over a 16 week period. We do not know exactly when the new algorithm will be in effect, but sometime after January 12, when Mark Zuckerberg posted the news on Facebook.
Instead of the mean number of likes for posts, I compare the median number of tweets for each week over the 16-week period. I prefer the median over the mean number of likes, because the distribution of likes is extremely skewed: a few posts receive extremely many likes and most of posts only receive a few likes (see for instance De Echo van Nederland). The median is a better measure for central tendency measure because it is incentive for these extremely popular posts. For now, I aggregated the data on a weekly basis to eliminate intra-weekly fluctuations (such as weekends versus weekdays).

Reviewing the first figure, we see that the weekly number of posts on Facebook is quite constant over the 16 week period.

in the second graph (below), the median number of likes fluctuates strongly. We particularly see a drop in week 9 in 2018. Could this be the result of the new news feed algorithm?

For a more detailed view, I prepared the same graph for different types of organization (below). Although all types of platforms have an online presence, they differ in terms of their origins. I distinguish newspapers, television, RTV (mostly radio stations and regional and local broadcasters) and online-only platforms. We see that newspapers publish the most posts, simply because there are many newspaper platforms. Radio, TV and online-only platforms roughly publish the same amount of posts.

Looking at the median number of likes for each type of platform, we see that TV posts on Facebook receive the most likes, while the other platforms receive considerably less likes for their posts. As for the variation across these 16 weeks, we see the strongest decrease in likes for TV news and current affairs programs. The online-only and RTV platforms also shows a slight decrease, while newspapers remain constant over time. Again, in week nine the number of likes declines. At the end of week 16 though, there seems to be some recovery as indicated by a slight increase likes. Whether this increase is persistent, time will tell.

In conclusion, if I were to make a guess when Facebook’s news feed algorithm changed, it would be week nine. Furthermore, it mostly affects news posts that are extremely popular, in this case posts by TV organizations and current affairs programs. Then again, there are many factors that affect the number of likes. So, this might be a continuing story….

Lecture series at University of Pisa on social media, political communication and journalism

A big thank you is in order. Last week I visited the department of political science, University of Pisa. Professor Roberta Bracialli invited me to give a number of lectures for her students about social media in politics and journalism, as well as to have some discussions with PhD-students. I really enjoyed doing the lectures, having the discussions on- and off-campus. Roberta Bracialli and her team do interesting stuff. Looking forward to seeing more of their output, and I hope we’ll be able to further our collaboration.

This visit was made possible by the Erasmus Plus program. So, if @CW_RU students might want to study at the University of Pisa, we have an exchange agreement. The city and student life in Pisa, from what I’ve seen, is very vibrant. Good food, nice bars, hanging out in the streets until late and nice concerts. Close by to excellent Florence. All in all, I really enjoyed my time in Pisa.

Thanks to Roberta Bracialli (@braccialer), Antonio Martella (@Vot4ntonio), Cesar Crisosto (@cesarcrisosto), Chiara Visentin (@ChiaraVis13) and Luca Corchia (@Luca_Corchia).

Call for applications: Theorizing and analyzing social media in political communication and journalism

Does your country have elections soon and you want to know how politicians and parties try to win your vote? Or are you interested how journalists use social media, and newspapers try to battle the declining subscription rates? And, on the side, want to learn the coolest analysis software that you can get for free? Well, then maybe this is the summer course you might want to sign up for.

Social media (such as Twitter, Facebook, YouTube, 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 lots of positive but mainly negative attention in the mainstream media as well as in the social sciences.
Social media research is concerned with determining how regular people (citizens), political actors (politicians, organizations) and media professionals (journalists) use social media to share opinions about issues, create online communities and use social media strategically to inform or to win over people, 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:

  • theorizing social media,
  • theorizing online journalism and political communication, and
  • 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 analyzing 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 program of the first week will focus on theory, although methods will also be a part of those sessions. The second week we will have hands-on meetings on how to collect social media data, how to develop measurements instruments and analyzing social media in terms of structure and content. We will use R as our tool for data collection, and data analysis. Data analysis will focus on basic statistical analysis (cross-tabulation, differences in means, regression analysis), content analysis and network analysis.

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 techniques. When discussing these theories and hypotheses, we will directly;
  3. In week two the focus will be on R as a 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 be able to find and install relevant packages;
  4. You will be able to perform basic analyses on social media data using R software. 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.

For who?
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 (cf. 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 behavior and online content, and do not eschew the occasional mathematical formula, this course is for you.
Even though it is not required to be experienced in statistics, having affinity with quantitative research as well have experience with using computers (cf. installing software) is considered helpful.
Your laptop
You will need to bring your own laptop. A laptop with the following requirements should be sufficient:

  • at least 4Gb RAM memory
  • running Windows 8.1 or higher, or a Linux (Ubuntu 14.04 or higher), Mac OS
  • wireless internet capability

Important dates

  • 1 April 2018: Deadline Early bird discount. If you apply before this date you will receive 10% discount or even 25% discount if you are studying at one of our partner universities
  • 1 June 2018: Application deadline
  • 6-17 August 2018: the course

For more information and applying for the course, please follow this link.

Oh yeah, so who will teach the course? That will be me, Maurice Vergeer. For more information on what I do, please check the rest of this blog and take a look at my publications.