Monetary policy communication: Uncovering central bank tweeting

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Vox EU

As central banks started to employ communication as a core part of their monetary policy toolkit in the early 1990s, they primarily targeted expert audiences such as financial market participants, academics, policymakers and specialised media, rather than the wider public (Blinder et al. 2005, Assenmacher et al. 2021, Blinder at al. 2022). Although this strategy has been largely successful in explaining monetary policy decision to expert audiences, communication with the general public has lagged behind (Ehrmann and Wabitsch 2021).

In recent years, major central banks are increasingly relying on the more direct channel of disseminating policycommunication through their websites and social media accounts. To this end, central banks have made their websites more user friendly – through, for example, educational resources and tools – and have also strengthened their presence on social media platforms such as Facebook, LinkedIn, and Twitter (Gorodnichenko et al. 2021, Ehrmann and Wabitsch2022). In a recent paper, we explore recent efforts by central banks to engage with a wider audience via Twitter (Masciandaro et al. 2022), which seems to be a channel that can likely influence macro phenomena, as political elections (Fujiwara et al., 2020).

Table 1 provides information on the number of followers recorded on the social media platforms of the G20 countries’ central banks as of September 2022. Twitter appears to be the most popular social media channel for most of the central banks, with the exceptions of the Reserve Bank of Australia, Bank of France, Bank of Italy, and the South African Reserve Bank, which are mainly followed on LinkedIn, and the Bank of Korea, which is more popular onFacebook.

Table 1 Central banks’ social media presence and followers (as of September 2022)

Note: The table presents data on the followers on social media platforms of G20 countries as of September 2022. The data is collected from the social media accounts advertised on the official website of these central banks. The European Central Bank is included as the central bank of the European Union. Whenever multiple profiles were advertised in relation to the same platform, the reported data only refers to the most followed account.

To provide more detail on how central banks use social media as a communication tool, we use the Twitter Academic API to extract all the Twitter messages generated by G20 central banks since the creation of their accounts. For each tweet, we extract the text, date and language of the tweet as well as the number of likes and retweets. We end up with a database of 215,011 tweets (excluding retweets) sent between June 2009 and September 2022.

Table 2 provides information on the number of tweets and other engagement statistics with the social media content of major central banks. Since joining Twitter in June 2010, the Bank of Indonesia has posted around 40,000 tweets andits number of social media posts is more than double that of the second most active central bank in our sample, the Bank of France. The Bank of Indonesia also has the highest number of replies to tweets by other users. However, with the exception of this central bank, on average, only 2.5% of the tweets of the other central banks are replies to othersocial media users.

Table 2 Central banks’ Twitter engagement statistics (as of September 2022)

Note: The table presents data on the number of tweets made by G20 central banks as of September 2022, together with the average number of likes and retweets received by their tweets. The data is collected using the Twitter Academic API. The European Central Bank is included as the central bank of the European Union. All retweets made by central bank in reaction to tweets made by other users have been excluded.

Yet, the number of tweets only measures the effort made by central banks to draw attention to their communication. Another important aspect to consider is the public engagement with the social media posts of central banks, which can be derived, for example, from the number of likes and retweets. The last two columns of Table 2 provide information on the average influence of the central bank tweets. The Saudi central bank has the highest average number of retweets per tweet, followed by the Bank of Japan, the Federal Reserve System and the ECB. The Bank of France, Bank of Korea and Bank of Russia have the lowest average engagement per tweet.

We then investigate the content of individual tweets to understand if certain topics are associated with a higher public engagement. To do so, we first translated all the tweets written in a language different from English by using Microsoft Translator (138,667 tweets, or 65% of the sample). We then extract a random sample of 5,000 tweets and manually classify them into nine different topics: banknotes, bulletins and reports, data releases and statistics, exchange rate information, monetary policy, other information, replies to tweets, research and conferences, and speeches and interviews.

After this classification, we compute the set of the most frequently used unigrams and bigrams terms for each topic, and we use them to further classify the remaining tweets. This procedure allows us to classify a total of 89,343tweets, or 42% of the sample.

Table 3 shows the distribution of the classified tweets across the different topics, together with the most frequent words associated to each topic. Using this classification and looking at the ten most liked and retweeted tweets, we find that all of them were made to announce the introduction of new coins or banknotes.

Table 3 Distribution of classified tweets by topic

Note: The table presents data on the number of tweets associated to the 9 topics identified in the classification of tweets. The last column shows the most frequent words in each classification.

Using these data, we analyse which topics are associated with greater public engagement. Our results suggest that banknotes announcements attract a disproportionally higher number of retweets as compared to tweets related to all other topics. In addition, tweets discussing monetary policy decisions and operations also attract a significantly larger reaction from Twitter users.

Overall, this suggests that the increased use of social media by central banks might represent an important tool to communicate monetary policy decisions. Indeed, the increased use of social media in central bank communication, together with the rising popularity of quantitative text analysis techniques, has given rise to a burgeoning literature that studies the role played by central bank social media communication.

All in all, our analysis confirms that central banks are increasingly engaging in social media as a regular feature of their communication policy. Future research can delve deeper into the analysis of high frequency social media content as a tool for measuring market expectations and the effectiveness of central bank communication. Another avenue for future research is the role of social media presence of monetary policy committee members, who have also significantlyincreased their efforts to engage with the wider public.


Assenmacher, K, G Glockler, S Holton et al….


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