Education policy research has for some time emphasised the increasing importance of intergovernmental organisations (IOs) in global education governance, not only through forms of ‘hard governance’ (e.g., instruments of funding), but also and especially through ‘soft governance’ (e.g., provision of epistemic knowledge or agenda setting) (Jakobi 2009; Zapp & Dahmen 2017). Scholars have shown that IOs exert great influence on national education policies by defining norms in various educational fields, such as Education for All (Chabbott 2003), lifelong learning (Jakobi 2009) or higher education (Zapp 2019; Zapp & Ramirez 2019). IOs use different media for agenda setting and dissemination of educational discourses, including more traditional forms such as reports, but also social media platforms such as Twitter for real-time communication (Bjola & Zaiotti 2021). While IO research often focuses on ex post forms of influence, that is, changes in education systems resulting from IO agendas, little attention has been paid on the emergence of education norms within IOs (Zapp 2019). In particular, previous research lacks information on the way in which norms and discourses move across different IOs. This study addresses this gap by examining education discourses in IOs based on Twitter data, and answers the following research question: How do educational discourses in IOs change over time and move across IOs?

The study draws on the concept of isomorphism, more specifically discursive isomorphism (Powell & DiMaggio 1983; Smith & Wiest 2012). According to the general idea of isomorphism, nation states tend to assimilate their educational discourses, policies, and structures over time (Meyer & Frank 2007). One reason for this process is the increasing influence of IOs: IOs disseminate specific educational norms and thereby lead nation states to adapt their education systems to these norms, at least in parts. This has been observed, for instance, in a stronger output orientation of German curricula due to the Programme for International Student Assessment (PISA) results of the Organisation for Economic Co-operation and Development (OECD) (Zapp & Powell 2016). However, these ideas neglect the inter-organisational relations between different IOs. IOs tend to align their discourses over time, especially in times of great challenges, as has been observed in recent years. I therefore argue that certain forms of isomorphism can be observed across education IOs as well.  Smith & Wiest (2012) define this process as “discursive isomorphism” and describe the tendency for political actors to adopt similar discourses and norms. One way of representing the discursive similarity between political actors is discourse networks, that is, graphical representations of actors and their discourses (Leifeld 2016).

The aim of this study is to map the discursive relations between education IOs over a fifteen-year period and to highlight significant changes that lead to the alignment and adaptation of discourses. The study shows how these shifting education discourses within IOs reflect a growing recognition of the complex and interconnected nature of the challenges facing education systems around the world. As such, they underscore the need for a holistic and multi-faceted approach to these challenges that goes beyond simply improving access to education to focus on issues such as quality, equity, and lifelong learning.

To answer the research question, an innovative combination of two research methods is used: topic modelling (TM; Wesslen 2018) of Twitter data and discourse network analysis (DNA; Leifeld 2016). TM can be briefly summarised as “an unsupervised machine learning algorithm that is being trained to discover a set of topics in a latent space derived from a corpus of documents” (Seitzer et al. 2021, p. 204). In this way, researchers can automatically define the topics discussed in large sets of documents and match these topics to sources. DNA, in turn, is a method to map and study the discursive connections between political actors. Discourse networks represent actors and their political concepts and beliefs within a specific topic, such as education. To create discourse networks, actors are assigned to different concepts. On this basis, two different forms of networks can be formed: one-mode and two-mode networks. Two-mode networks consist of actors and concepts, where the nodes of the network represent either actors or concepts and the connections represent approval. Thus, if an actor A approves concept C, A and C are connected. In contrast, one-mode networks consist only of actors connected by shared concepts. In other words, if actors A and B approve the same concept C, A and B are connected. The study of the emerging networks makes it possible to identify discourse coalitions of actors who follow the same discourses (Leifeld 2016). In this way, combining the two methods allows for a systematic analysis of discourses based on large amounts of data. Previous research on education discourses in IOs has mainly relied on official documents (e.g., Zapp 2019; Seitzer et al. 2021). However, these documents are published irregularly and often cover a wide range of topics. In contrast, social media data such as Twitter allow us to capture information published by IOs in real-time. This study thus draws on Twitter data to identify education discourses in IOs. All Tweets published by education IOs (according to Niemann & Martens 2021) since the first Twitter registration of an IO in 2008 and related to education were collected. For a longitudinal analysis, tweets from 2009 and 2010 (combined due to low numbers), 2014, 2018 and 2022 were modelled using Latent Dirichlet allocation to identify different topics. The topics were then related to the IOs and translated into one-mode and two-mode networks for each of the four years.

The one-mode networks show leading IOs, such as UNESCO, UNICEF, and World Bank, as well as some regional organisations (e.g., the Asian Development Bank) positioned at the centre of the discourse networks, while mainly regional organisations alongside the International Labour Organization and United Nations High Commissioner for Refugees are at the margins. At the same time, some regional organisations (e.g., ICESCO) are moving to the centre over time and seem to be adopting more of the common discourses. This can be seen as a form of discursive isomorphism among IOs that are less powerful at the international level. The analysis of the different discourses addressed in the tweets shows that the future of youth through training of certain skills, developmental aspects, inclusion and gender equality, and global partnerships are recurring topics that are at the centre of the two-mode discourse networks. It is particularly noteworthy that the global partnership discourse serves as a ‘bridging narrative’ that integrates partially excluded IOs into the main network. Such organisations (e.g., Commonwealth) take over mainstream topics in the following years and show that they have adapted to newer discourses such as gender equality and the importance of specific skills for a successful future. Overall, these preliminary findings suggest that IOs tend to adapt discourses of other IOs, especially those of the “Big Five” (Zapp & Dahmen 2017), mainly UNESCO, UNICEF and the World Bank. This process is particularly evident in regional organisations, which seem to lag behind some of the newer discourses promoted by these leading organisations. At the same time, little discursive variance is observed among more influential IOs. This indicates that the influential IOs tend to change their education discourses simultaneously within a short period of time, while the less powerful IOs adapt slowly over time and show discursive isomorphism.

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