Echoing Gejayan’s Call: Twitter and youth mobilization for political protest

By Paska Darmawan

On the 23rd of September, students and other protesters all across Yogyakarta marched down the Gejayan street to voice out their concern against several problematic bills that were on the edge of being passed by the Indonesian parliament. Activists are using social media to spread information about the protest. They posted jargons, demands, and digital posters using the hashtag #GejayanMemanggil (translation: Gejayan is calling) to persuade people to join the protest. As a result, there was a huge turn out of people joining the protest even though the first tweet was only posted the day before, on September 22, 2019 at 00:15:56 local time.

The use of Twitter for mass mobilization has been well discussed since last decade. There are multiple cases where Twitter plays a huge role in mobilizing people, such as the #Occupy movements (Gleason, 2013; Penney and Dadas, 2014; Tremayne, 2014), Arab Spring (Streinert-Threlkeld, 2017), and youth protests in South Africa (Bosch, 2017) and Austria (Maireder and Schwarzenegger, 2012). Twitter makes it much easier for protest organizers to mobilize people due to its design as a social networking site (SNS). Twitter limits the number of characters in a post, which forces people to compose short and direct posts. Twitter also allows users to forward a public post easily by retweeting it to their followers. These two features facilitate quick and massive diffusion of messages, which may attract support from other communities that are not directly affiliated with the protest (Boyd et al., 2010; Recuero et al., 2019).

In these previous cases, we can see that it took a while for the organizers to raise public’s awareness and convert people’s interest into active participation in real life. However, the Gejayan protest successfully garnered more than 40,000 tweets under its #GejayanMemanggil (translation: Gejayan is calling) hashtag within 24 hours, which led to a huge turn out despite the short notice. This raised a question on how information about the protest was spread rapidly on Twitter.

To answer that question, this research has analyzed tweets containing the hashtag #GejayanMemanggil that were posted on September 22, 2019. In total, there are 48,574 tweets collected for this research. Social network analysis (SNA) was conducted to identify the clusters of conversation by using the modularity algorithm, and to measure the influence of each user by using their in-degree centrality. Qualitative content analysis (QCA) will also be used to analyze the topics of conversation within the hashtag.

The Rapid Spread of #GejayanMemanggil

Based on our data, the first post containing the hashtag was tweeted on September 22, 2019 at 00:15:56 WIB (Western Indonesia Time). We tried to collect tweets using #GejayanMemanggil prior to September 22, but the search returned no result. The first tweet was posted by @mahasiswaYUJIEM, but it did not gain many responses from other users. As of October 9, 2019, it only has 2 retweets and 1 reply.

Avatar Twitter ga mau samaan nih? Yuk gas #gejayanmemanggil

— Si Ji Em (@mahasiswaYUJIEM) September 21, 2019

The hashtag, however, started to blow up when the same account posted a giveaway for those who retweet and/or like their post. The post, and other subsequent posts in the thread, also contain digital posters about the protest. As of October 9, 2019, the post ended up having 784 retweets and 750 likes.


GIVEAWAY ini untuk 2 orang yang beruntung, syaratnya mudah cukup RT dan Like aja.

Pengumuman pemenang dipost hari senin 23/9/19 malam pukul 11

Goodluck, semangat #GejayanMemanggil #Giveaway

— Si Ji Em (@mahasiswaYUJIEM) September 21, 2019

When we take a look at the number of tweets over the hours, we can see that the hashtag started garnering more attention after noon. The post count had begun to gradually increase until around 9 p.m., where it peaked with a total of 6,756 tweets.


From noon until midnight, there are a total of 16,190 tweets, of which more than 82% are retweets. That being said, we decided to go deeper to look at what tweets are being retweeted the most within this time span. Based on Figure 2, we can see that most of these tweets encourage people to join the protest, which explains how Twitter helped the spread of information to wider audience.

Visualization below helps us understand how information spreads from one user to another. We analyzed interaction network within #GejayanMemanggil by using dynamic network analysis. From this graph, we can see how there are several key accounts whose tweets reach greater audience in less than 24 hours as their tweets got retweeted (and to a much smaller extent, replied to). The visualization is color coded based on their modularity class, which we will explain in the next section. One important thing to underline is how this hashtag is driven not only by a few influential users with high number of followers (e.g. BukuMojok, BerdikariBook), but also by other users whose reach of their tweet far exceeds their follower count (e.g. panjipnjk, tempelan_kulkas)

Graph 1. Dynamic Interactions within #GejayanMemanggil

The Presence of Separate Agenda

We grouped #GejayanMemanggil users by using modularity algorithm (see Blondel et al., 2008) to identify different clusters within the whole network. As a result, we have identified seven major clusters with coverage of more than 5% each. In the visualization, we have filtered out other clusters within the network for clarity.

Graph 2. Major Clusters within #GejayanMemanggil Network

From Graph 2, we can see that most of these clusters have similar shapes. Almost all of them are quite centralized, with only one key account that acts as the source of information, represented by the bigger size of their circle and label. However, the graph shows that cluster #4 is more decentralized and has quite different structure compared to the other major clusters.

Graph 3. Structure of Cluster #4

If we look closely at Graph 3, we will see that cluster #4 has a few main users who do not have significantly higher degree (number of connections) compared to other users in the cluster. This confirms our finding that cluster #4 is more decentralized and has different structure compared to the other major clusters, whose network is dominated by one key account.


The difference between cluster #4 and the other clusters motivated us to identify top account and top post from each cluster. From Table 1, we can see that most of these top tweets have direct relevance with the protest by either declaring their participation, explaining about the urgency, or attaching visual media related to the protest. On the other hand, the top tweet from cluster #4 by @Anggraini_4yu brings in issues related to religious sentiment and the re-emergence of PKI (the now-defunct Communist Party of Indonesia), which are not directly relevant with the demands of the protest.


To further see the different contents, we grouped all tweets based on their cluster and identified the most frequent words being tweeted in each group. As we can see, most of these clusters contain similar words, except for cluster #3 and #4. For cluster #3, most of the tweets contain words like "giveaway", "goodluck", and "beruntung" (lucky) due to giveaway post from mahasiswaYUJIEM that got retweeted by many other users. The other most-frequently mentioned words, however, are still much related to the protest. On the other hand, words that have no direct correlation with the protest, such as "kamboja" (Cambodia), "PKI/komunis" (communist), Alquran, and Muslim become the most frequently mentioned words in cluster #4. This finding further confirms how users in cluster #4 are trying to push another agenda by riding on the hashtag.


From the analysis, we can find that activists and student-run university accounts played a huge role in spreading the information. They became key opinion leaders by posting about information regarding the demands and the technical details of the offline protest. A smaller number of users that were not in direct affiliation with the organizer of the protest also garnered a huge level of indegree by posting memes and also screenshots from their lecturers that give students permission to join the protest. However, there are also some political influencers who attempted to free ride on the hashtag and push another agenda that is unrelated to the protest. However, the number of these intruders were small, mostly because of the short timespan between the start of the hashtag and the offline protest.

As mentioned previously, top users mostly tweeted their call to join the protest. These tweets received high number of engagements, which shows positive reception of Twitter users towards the call. Other top tweets include informative and/or entertaining contents about the protest, such as digital posters and memes. There are insignificant numbers of tweets that react negatively towards the protest. There are also several tweets within the hashtag that are irrelevant towards the protest, such as promotional tweets and tweets about the Indonesian Communist Party (PKI) that were posted by some political influencers that try to use the hashtag to push their own agenda.

This research was previously presented at a webinar with Manchester Metropolitan University on May 18, 2020