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).

Radboud Summer School course “Social Media Theory and Data in Journalism and Political Communication”

I am pleased to announce that I will teach a course on social media theory and data in journalism and political communication. It will take place in the first week of August 2016 in Nijmegen, the Netherlands. Click to read the course description.

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).
A subdivision of social media research concerns how regular people (citizens), political actors (politicians, organisations) 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 this 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 theories about online journalism and political communication, and (c) methods of data collection and analysis of social media.
Social media theories will look at the specifics of social media design and how this affects online communication and networks. This theme is applicable to all kinds of social media and connected digital media. Subsequently we will look at creating social media theories for journalism and political communication using traditional and new approaches to create social media theories such as agenda setting research and networked journalism. Furthermore, we will discuss and use methods of collection and analysing social media data. The 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) and the actual content of social media (i.e., expressed opinions).
In the morning programme the main focus will be theory, although methods will be a part of those sessions. In the afternoon we will have hands-on meetings on how to collect social media data, how to develop measurements instruments and analysing social media in terms of structure and content.

General information about summer courses from the Radboud University in 2016 can be found here.