Abstract
Online engagement is key to sustaining online connective action over time. However, there is limited research on how social media messages can trigger diverse connective actions, quantifying more precisely the different forms of online engagement generated with social protest, especially those related with environment and climate change. To this end, this study analyses a random sample of tweets containing #fridaysforfuture to identify which message characteristics motivate people to engage online in the digitally networked action against climate change. Results evidence that depends on who send messages (Greta Thunberg and icon-influencers), what content (“not supporting the movement” and “information about COVID-19 and digital strikes”), when (during business hours), and how (audiovisual format and other hashtags), higher levels of online engagement with #fridaysforfuture are generated via retweets, cited tweets, likes, comments, and replies to comments. This study contributes to previous literature expanding the empirical applications of the connective action theory, using a broader and deeper metric of online engagement with social movements, and providing a bigger picture on the debate on the importance of message strategies to generate higher engagement with social protest. This research offers implications to optimize message design, fine-tune communication strategy in general, and, in the case of social movements, to reinforce digitally networked action.
Keywords
Introduction
Environmental activism using hashtags is a key part of understanding the emergence of new forms of social movements, such as the current “connective” environmental movements that prevent and alert in relation to climate change. Hashtags serve as an indexing system on social media, enabling people to access and participate in protests concerning social and political issues (Rovira-Sancho, 2023). Through a post containing a hashtag, an individual can digitally engage with a protest via actions such as liking, commenting, and sharing contents (Shahbaznezhad et al., 2021). This article aims to analyze how to foster online engagement with climate change via hashtag activism on Twitter under the lens of connective action, a framework that theorizes on individuals’ digital actions and impacts taking place on online social media platforms, in the context of an online social movement (Bennett & Segerberg, 2012).
Previous studies have evidenced the importance of personal communication on social media and individual connective action for participating in social movements (Bernroider et al., 2022; Gunster, 2022). However, still more knowledge is needed to understand how individuals engage with a digitally networked action (Lukito et al., 2023; Uwalaka & Nwala, 2023). In this sense, scarce is the literature that deepen on how social media messages can trigger diverse connective actions, quantifying more precisely the different forms of online engagement that facilitate citizens participation in protests (Cheng et al., 2024). Previous studies have mainly explored the connective action of retweeting or sharing of information by people engaged in social protests, for example against the political regime in some countries (Lukito et al., 2023), police brutality (Wang & Zhou, 2021), racism (Bernroider et al., 2022), and in favor of women’s rights (Mirbabaie et al., 2021). The research related to environmental protest is mainly focused on environmental disasters in emergency situations (Vaast et al., 2017; Zhang, 2023).
To fill this gap in the literature, this study examines the role of several post characteristics in generating online engagement, drawing on data from 1613 tweets that include #fridaysforfuture. These post characteristics are classified according to the traditional “5Ws + 1 H questions method” (i.e. why, where, who (i.e. sender and influencer types), what (i.e. message communication functions or content type), when (i.e. posting day and posting time), or how these contents are published (i.e. content format, such as text, photo/image, video/gif, and other hashtags usage)). Likewise, the online engagement is explored from both at an aggregate level, as a sum of five forms of online engagement (retweeting, citing, liking, commenting, and replying to comments); and disaggregated, that is, exploring which posts characteristics influence each of the aforementioned online engagement forms.
Results revealed that there are statistical differences in the user interactions analyzed between tweet characteristics regarding who, what, partially when, and how questions. In particular, Greta Thunberg and icon-influencers (with more than 1,000,000 followers), content type related to “not supporting the movement” and “information about COVID-19 and/or digital strikes,” posts published during business hours, formats of “text and video,” “text and image,” and tweets containing other hashtags “not related to sustainability and related to COVID-19,” and “related to COVID-19,” all generate more online engagement than other categories. However, tweets published during weekdays only receive more retweets, cited tweets, and comments than tweets published during weekends.
This study contributes to the literature on social media communication in several ways. First, this study expands the empirical research on the application of connective action theory to understand what message conditions help individuals to express their opinions on social protests and reach the attention of others individuals, thereby generating more connective action. Second, another contribution of the proposed study is the usage of a broader and deeper metric of online engagement with social movements compared to those used in previous studies (e.g. Cheng et al., 2024), including in our study five different online engagement forms. Third, it responds to the call of studies that provide a bigger picture on the debate on the importance of message strategies to generate higher online engagement with social protests (Zhang, 2023) and how online activism can be more than just a single wave, but rather a sustained flood consistent over time (Mede & Schroeder, 2024). In particular, this study goes in depth into five key message dimensions: who, what, when, and how these contents are published to obtain an online productive engagement. Finally, our findings could help both informal and formal forms of organization to become aware of the importance of the power of a fine-tune message strategy to impact on our current network society.
Online engagement and connective action
The concept of engagement has gained considerable attention in academic research in recent years, with the consequent development of different definitions, insights, and arguments to delimit this term. In this sense, different conceptualizations of engagement vary based on several criteria, which are (1) researchers’ perspective (attitudinal and behavioral); (2) focal object or actor of engagement, also called engagement typology (brand, customer or user engagement); (3) engagement scope (lucrative or non-lucrative settings); (4) context of engagement (social media, brand communities, or websites); (5) engagement valence (negative or positive); and (6) intensity of engagement (passive, that is, views, or active, that is, commenting; Shahbaznezhad et al., 2021).
The present study focuses on the behavioral perspective of users’ online social media engagement within the scope of connective action in a non-transactional or non-lucrative context, as is the Fridays for Future (FFF) social movement, involving both positive and negative engagement behaviors generated on Twitter. Therefore, within these constraints, engagement can be defined as a “set of actions or reactions that users take on social media in response to a specific content published (e.g. likes, comments, shares)” (García-de-Frutos and Estrella-Ramón, 2021, p. 92) and that “create a connective action among like-minded individuals” (Hopke & Paris, 2022, p. 3).
The logic of connective action can help to understand behavioral engagement in online social movements, such as FFF, as actions such as liking a comment or posting a hashtag on an online social platform are considered connective actions (Cheng et al., 2024; Gunster, 2022; Merrill & Copsey, 2022; Pandey et al., 2020). This approach is centered on how large-scale, unstructured online protests can emerge among social media users, with the viral dissemination of mobilizing messages and without social movement organizations playing a central role. Unlike collective action, which features strong organizational coordination of actions (Oktavianus & Davidson, 2023), in the case of connective action, traditional organizations are either absent or only loosely responsible for coordination, which also reduces hierarchies among social movement participants (Bennett & Segerberg, 2012). This framework recognizes digital media not just as mere platforms but as organizing agents that allow individuals to share information and ideas about a specific social issue absent of hierarchical leadership (Bennett & Segerberg, 2012). In this sense, Connective Action Theory describes how activists use online social media, as an organizing agent, to share their interest in social movements and to be engaged in digitally networked actions (Mirbabaie et al., 2021; Uwalaka & Nwala, 2023). Thus, behavioral engagement on social media is comprised of the actions of individuals that generate network connections, as well as those that have an impact within a social media digital platform (Shahin et al., 2021; Wang & Zhou, 2021).
There is a need for further knowledge on how connective actions take place (Showden et al., 2023), including other actions apart from sharing information (retweeting) (Mirbabaie et al., 2021; Shahin et al., 2021). Hence, this research contributes to an in-depth understanding of online engagement in those individual connective actions (including retweets, cites, likes, comments, and replies to comments) carried out for people to engage with social movements on climate change on social media through hashtag activism.
Answering the traditional “5Ws + 1 H questions method” using connective action
Why and where posts containing #fridaysforfuture are published?
The reason why social movements on climate change utilize social media is mainly to mobilize citizens toward connective actions aiming to create a change in society (Baran & Stoltenberg, 2023; Bennett & Segerberg, 2012). These digital platforms are spaces where citizens, as social movement participants, carry out the organizing and communication functions necessary to achieve their goals in their protests for environmental and climate justice. Regarding their organizational function, these platforms enable like-minded individuals to connect with each other across time and space divisions, allowing the more rapid diffusion of social movement tactics and coordinated campaigns (Hopke & Paris, 2022). With respect to its communication function, social media fosters social movements’ public visibility, helping to gain media attention, which is an essential precondition to convince the public of their grievances, validate their legitimacy, and mobilize potential supporters (Mede & Schroeder, 2024). Previous research has noted that environmental activists are using these platforms as channels for activist actions, such as protesting, boycotting, and signing petitions (Baran & Stoltenberg, 2023; Boulianne & Ohme, 2022).
Twitter is considered a central “protest space” where people become active participants in environmental and social issues (Merrill & Copsey, 2022) albeit other online platforms also are being used (Nguyen-Van-Quoc et al., 2024; Uwalaka & Nwala, 2023). The Twitter hashtag is considered an important space for initiating social movements’ connective actions and a key digital feature for the understanding of the communication strategies in climate change activism (Pearce et al., 2019). Hashtags were initially introduced on Twitter as a user-initiated practice to categorize—or tag—posts as belonging to a specific group, topic, or discussion, albeit they are now also used on other social media platforms (Wonneberger et al., 2021). Nowadays, people use hashtags for several motives, such as amusing, organizing, designing, conforming, trend gaging, bonding, inspiring, reaching, summarizing, and endorsing (Rauschnabel et al., 2019), proving to be an excellent space for so-called “hashtag activism” (Baran & Stoltenberg, 2023; Wonneberger et al., 2021). This term refers to the “act of fighting for or supporting a cause with the use of hashtags as the primary channel to raise awareness of an issue and encourage debate on social media” (Tombleson & Wolf, 2017, pp. 15), such as awareness on climate change.
In keeping with this line, the FFF social movement uses social media to organize transnational public engagement in terms of youth participation in weekly decentralized events and occasional Global Climate Strikes (Svensson & Wahlström, 2023). Similarly, it is also used to gain media visibility and, consequently, to achieve an amplified transnational reach that captures the attention of international media, policy makers, and society in general. This occurs thanks to the effects of disruptive social media virality, since social media made it possible for an underrepresented population (such as youth) to connect across the globe, granting them more rapid diffusion and influence to urge policymakers to take interest in their message (Hopke & Paris, 2022). Twitter has been one of the main protest spaces featuring #fridaysforfuture, facilitating its inception, but also allowing it to maintain public interest in the movement years into the future, for example, during the lockdown caused by COVID-19 (Mede & Schroeder, 2024).
However, the mere use of a hashtag on Twitter is not enough to motivate people to engage in FFF (Zhang, 2023). To truly make people participate in a social cause, either online or offline, an effective online communication strategy is needed (Haßler et al., 2021). In this regard, previous literature has noted the need for further knowledge to understand online engagement generated by hashtag activism (Baran & Stoltenberg, 2023; Cheng et al., 2024; Wonneberger et al., 2021). Delving into aspects such as who publishes contents (i.e. sender and influencers types) (Mirbabaie et al., 2021; Zhang, 2023), what contents are published (i.e. message communication functions or content type), when these contents are published (i.e. posting day and posting time), or how these contents are published (i.e. content format and other hashtags usage) to foster active participation in posts using hashtags generates a substantial research gap (Pearce et al., 2019).
FFF is unique because it became a global climate movement thanks to social media and mobile technologies. Its novelty prompted several studies to examine this social movement to explain disruptive social media virality (Hopke & Paris, 2022), while others have explored how this social movement has maintained its legitimacy through the online activity of tweets and retweets (Haßler et al., 2021), the use and connection of hashtags related to FFF on Instagram (Herrmann et al., 2022), or focused on the leader Greta Thunberg and her social media usage for fostering citizen’s engagement with FFF movement (Mede & Schroeder, 2024). Nevertheless, still little attention has been paid to provide a wider picture on the aspects (i.e. who, what, when, and how) that explain why #fridaysforfuture posts have been so successful at receiving online engagement, which is precisely the gap that this study aims to address.
Hypotheses development regarding who, what, when, and how
Who publishes contents (sender and influencer types) that generate more engagement?
From the connective action perspective, actors are those elements that are loosely connected through a technological platform (such as social media) and contribute to a shared goal, reducing hierarchies and leadership among participants in social movements (Bennett & Segerberg, 2012). These actors, by means of the digital network, contribute to the spreading of the social movements’ messages, especially when these messages contain a hashtag. Indeed, the connective action for social movements on social media is facilitated by hashtag activism, as it fosters autonomy and self-organization of the social movement participants (Uwalaka & Nwala, 2023).
However, to achieve connective action, there are different key actor types that assume different roles with varying involvement in the task of spreading messages (Cheng et al., 2024; Mede & Schroeder, 2024). For example, Alatas et al. (2019) found that celebrities hold an important role within social media-driven social movements because they have endorsement power, which means that those tweets that users identify as created by a celebrity obtain more likes or retweets than similar tweets without this identification.
In addition to celebrities generating engagement, Mirbabaie et al. (2021) also identify the top power users or roles of the #metoo social movement as those participants who receive the highest number of retweets within a network, who are mainly private individuals (i.e. ordinary citizens), journalists (both private and public), media organizations (i.e. newspapers and TV companies), and activists (i.e. publicly declared social activists). In a similar vein, Wang and Zhou (2021) differentiated between information generators (actors who actively generate contents) and information drivers (actors who actively share contents and are connected with other more active users in the information-sharing network), who consequently generate more engagement and connective action. Therefore, it could be expected that depending on who sends the messages containing #fridaysforfuture, there could be differences in the level of user engagement and, consequently, the connective action generated.
H1. There are differences in engagement generated by posts containing #fridaysforfuture on Twitter (i.e. retweets, cited tweets, likes, comments, and replies to comments) depending on sender type and influencer type.
What contents (message communication functions or content types) generate more engagement?
Connective action via social media is generated mainly by self-motivated activists that use these online platforms to exchange personalized content that drives participation in collective action to focus attention, without the requirement of a collective identity or the organizational resources (Bennett & Segerberg, 2012). However, the original concept describing a synergetic “mass-production” of personalized content (Bennett & Segerberg, 2012) should be investigated further to determine how activists’ discursive strategies prompt online and offline connective actions (Bernroider et al., 2022).
Not all narratives seem to have the same ability to successfully encourage other individuals to participate in connective actions through social media (Clark-Parsons, 2021; Lukito et al., 2023). In this respect, Wang and Zhou (2021) examine the type of content that established network connections among the activists who used #HongKongPoliceBrutality, revealing that those informative messages that documented evidence related to police brutality generated higher online connective actions, in terms of frequency of retweets. Examining the #metoo movement, Mirbabaie et al. (2021) state that tweets containing a testimony were more likely to be retweeted. Moreover, Shahin et al. (2021) analyze the diffusion of the social movement Black Lives Matter, via several hashtags related to #GeorgeFloyd, highlighting people’s engagement with messages of support in harmony with the values of the movement, such as messages of solidarity generated.
Hence, it would be logical to expect that depending on what message communication functions or content types characterize the messages containing #fridaysforfuture, there could be differences in the level of user engagement and, consequently, the connective action generated.
H2. There are differences in engagement generated by posts containing #fridaysforfuture on Twitter (i.e. retweets, cited tweets, likes, comments, and replies to comments) depending on message communication function or content type.
When contents (posting day and posting time) generate more engagement?
When a post, with an activist hashtag, has greater or lesser public engagement is an aspect to address, as the activity and interactions that occur on social media vary over time (Cheng et al., 2024; Vaast et al., 2017). In this regard, by considering two different time periods, Mirbabaie et al. (2021) found that the level of engagement around the #metoo debate varied over time. Moreover, the influence of day/time is especially pronounced on Twitter because of its function of real-time interaction via retweeting.
Although the connective action framework seeks to understand the most remarkable aspects that sustain the action networks (Bennett & Segerberg, 2012), the analysis of connective action generated by day and time when posts are published has yet to be quantified. Previous literature has focused on online engagement, but only in organizational terms, highlighting that in fast-moving consumer goods companies (Pletikosa-Cvijikj & Michahelles, 2013) and travel agencies (Sabate et al., 2014) posts created on weekdays and during business hours receive a higher level of engagement, while in public destination management organizations, the most public engagement occurs outside of working hours and at weekends (Gálvez-Rodriguez et al., 2020).
Considering the literature reviewed, we can expect that in the digital network around climate change protest, such as #fridaysforfuture, there could be differences in the online engagement generated depending on the posting day and posting time.
H3. There are differences in engagement generated by posts containing #fridaysforfuture on Twitter (i.e. retweets, cited tweets, likes, comments, and replies to comments) depending on posting day and posting time.
How are contents published (content format and other hashtags usage) to generate more engagement?
The logic of connective action emerges from the analysis of individuals’ “personalized communication” that engages with social movements using different communication technologies, such as social media, to share common concerns on social issues (Bennett & Segerberg, 2012). In this regard, people not only use text messages in their communications, but also other formats. Indeed, different formats have been used in hashtag activism, such as photos, videos, or hyperlinks, to ensure that the meaning of the message is understood (Shahin et al., 2021), but also to foster emotions and feelings toward the core value of the protests (Uwalaka & Nwala, 2023).
Although few studies have focused on message format and connective actions via online engagement, previous authors observe that in environmental social movements, such as the protest related to the Gulf of Mexico Oil Spill, the use of links in tweets encouraged public online engagement (Vaast et al., 2017). Moreover, Mirbabaie et al. (2021), focusing on a social protest, identified that messages in social media containing any picture or video were more likely to be retweeted. Therefore, it would be logical to expect that depending on how the format in the messages containing #fridaysforfuture is used, there could be differences in the level of online engagement and, consequently, the connective action generated.
H4. There are differences in engagement generated by posts containing #fridaysforfuture on Twitter (i.e. retweets, cited tweets, likes, comments, and replies to comments) depending on the message format and other hashtag usage.
Figure 1 summarizes the proposed hypotheses.
Summary of Figure 1. Summary of the proposed hypotheses.
Materials and methods
Sampling and data collection
A total of 555,760 tweets published between March 2020 and February 2021, containing the hashtag #fridaysforfuture and written in English, were collected using the tool called TAGS v6.1.9.1 (http://tags.hawksey.info/about/) and the Twitter API. TAGS tool identifies the different attributes of each tweet, such as the text of the tweet, its URL, date and time the tweet was created, if the tweet is a retweet/reply, the username who published the post and his or her number of followers. Retweets and replies were removed, and the resulting database contained 33,451 tweets. In addition, a random sample of 6% of posts left in the database was extracted, and the resulting database contained 2049 tweets. This sampling process was carried out as some of the variables considered required the manual handling of the posts collected to complete the database, such as the identification of sender type, message communication function, format, other hashtag usage, as well as the quantification of the interactions received. This manual handling was carried out between April 2021 and March 2022, allowing for a delay between tweet publication time and database completion, necessary to capture how users interact with the tweets already published. Three coders carried out manual handling and completion of the database. Discrepancies between two coders were examined and solved by the third coder. Intercoder reliability is higher than the minimum threshold (reliability = 0.85 > 0.80 minimum threshold) (Holsti, 1969). Finally, tweets that were not available or did not have interpretable content were removed from the database, with 1613 tweets remaining.
Measurement of variables
To collect dependent and independent variables properly, coders used a coding instrument elaborated based on previous research and on inductive examination of Twitter. The coding instrument was pretested on a sample of Twitter posts not included in the final sample, which allowed for a clearer definition of the variables to be included in the final coding manual.
The dependent variables in this study are a set of continuous variables representing user engagement with posts/messages published on Twitter and the different user interactions that comprise engagement (Yang et al., 2022), which contribute to spreading social movements and reinforce connective action (Pandey et al., 2020). The user engagement data collected consist of number of retweets, cited tweets, likes, comments, and replies to comments (adapted from Dimitrova et al., 2022). The engagement measure is calculated as the sum of these different user interactions (adapted from Yang et al., 2022).
With respect to independent variables, the database includes a set of categorical variables to measure sender and influencer types (Israel-Turim et al., 2021), message communication functions of social movements (adapted from Stein (2009), posting day and time (Sabate et al., 2014), message format, and other hashtag usage (Shahbaznezhad et al., 2021). The coding manual is shown in Table 1 for these independent variables and provides operational definitions and the coding strategy followed to collect these variables.
Coding instrument for independent variables.
Statistical analysis
The Kruskal–Wallis test is applied to solve the hypotheses proposed. This non-parametric statistical analysis technique is the most appropriate for analyzing two independent samples for which the grouping variable is categorical (i.e. sender and influencer types, message communication functions, posting day and time, message format, and other hashtag usage), and the dependent variables (i.e. online user engagement) do not comply with the assumptions of normality and homoscedasticity. Descriptive statistics and the Kruskal–Wallis test results are shown in Tables 2 to 8.
Descriptive statistics and Kruskal–Wallis H results for sender type (who).
Descriptive statistics and Kruskal–Wallis H results for influencer type (who).
Descriptive statistics and Kruskal–Wallis H results for message communication social movement function (what).
Descriptive statistics and Kruskal–Wallis H results for posting day (when).
Descriptive statistics and Kruskal–Wallis H results for posting time (when).
Descriptive statistics and Kruskal–Wallis H results for message format (how).
Descriptive statistics and Kruskal–Wallis H results for other hashtag usage (how).
Results
Sender and influencer type (who)
The results indicate that there are significant differences in engagement depending not only on sender type (H = 277.08, p < 0.05) but also on influencer type (H = 609.19, p < 0.05), completely supporting H1. The results also indicate that there are significant differences between different connective actions analyzed and sender type (for the actions of retweeting H = 273.35, p < 0.05; citing tweets H = 330.97, p < 0.05; liking H = 270.44, p < 0.05; commenting H = 269.85, p < 0.05; and replying to comments H = 518.27, p < 0.05). In addition, there are also significant differences between different connective actions and influencer types (for the actions of retweet H = 569.47, p < 0.05; cite tweets H = 562.79, p < 0.05; like H = 580.59, p < 0.05; comment H = 409.77, p < 0.05; and reply to comments H = 420.70, p < 0.05). For more details about these results, see Tables 2 and 3.
Regarding sender type, the rank analysis reveals that, considering total engagement, the posts sent by Greta Thunberg received the highest level of engagement, followed by those posts sent by non-governmental organizations (NGOs) and the FFF movement. Greta Thunberg also received the highest engagement considering the different connective actions analyzed. However, the FFF movement and NGOs take the second and third positions in the case of retweets, tweets cited, and number of likes and comments. In addition, the posts with the most replies to comments, apart from those by Greta Thunberg, are also those from the FFF movement and individuals/citizens. With respect to the results on influencers, the rank analysis indicates that those influencers with more than 1,000,000 followers, called icon-influencers, received the highest level of engagement, followed by macro-influencers (between 100,001 and 1,000,000 followers) and mid-influencers (with 10,001–100,000 followers). This finding is similar both in total public engagement generated and in the different connective actions analyzed. For more details about different categories, mean rank analysis results are shown in Figures 2 and 3.
Sender-type mean rank analysis.
Influencer-type mean rank analysis.
Message communication social movement function (what)
Results indicate that there are significant differences between engagement generated by posts containing #fridaysforfuture on Twitter and content type or message communication functions of social movements (H = 69.50, p < 0.05), supporting H2. In addition, there are significant differences in the different connective actions analyzed and message content type (for the actions of retweets H = 58.18, p < 0.05; cite tweets H = 52.06, p < 0.05; likes H = 71.67, p < 0.05; comments H = 63.89, p < 0.05; and replies to comments H = 54.48, p < 0.05). More details are included in Table 4.
The rank analysis shows that in most cases the content type related to “not support the movement” and “information about digital strikes and/or COVID-19” generates more engagement, holding both first and second position, or vice versa, in the different connective actions analyzed. The third position varies depending on the connective action that each content type stimulates most: messages that promote fundraising and resource generation encourage more actions of retweeting, posts containing information about FFF and sustainability result in more citing tweets, posts with creative expressions produce more actions of liking and replying to comments, and posts encouraging action generate more actions of commenting. For more details about different categories, mean rank analysis results are shown in Figure 4.
Content-type mean rank analysis.
Posting day and time (when)
Results indicate that there are not significant differences in the total engagement achieved depending on posting day (H = 2.92, p > 0.05). However, results indicate that there are significant differences in the total engagement achieved depending on posting time (H = 7.52, p < 0.05), partially supporting H3. For more details, see Tables 5 and 6.
Delving further into the different connective actions analyzed, the results indicate that there are significant differences between posting day and the actions of retweeting (H = 5.34, p < 0.05), citing tweets (H = 8.94, p < 0.05), and commenting (H = 4.04, p < 0.05). There are non-significant results between posting day and the actions of liking (H = 1.60, p > 0.05) and replying to comments (H = 3.67, p > 0.05). In cases with significant differences, the rank analysis reveals that posts published during weekdays receive higher user engagement with FFF networked action in terms of retweets, cited tweets, and comments than posts published during weekends. Results also indicate that there are significant differences between user engagement analyzed and posting time (for actions of retweeting H = 4.50, p < 0.05; for citing tweets H = 11.59, p < 0.05; for liking H = 10.02, p < 0.05; for commenting H = 7.62, p < 0.05; and for replying to comments H = 10.11, p < 0.05). The rank analysis indicates that in all cases posts published during business hours generate more user engagement with the FFF networked action than posts published during non-business hours. For more details about different categories, mean rank analysis results are shown in Figures 5 and 6.
Posting day mean rank analysis.
Posting time mean rank analysis.
Message format and other hashtag usage (how)
There are also significant differences between total engagement and message format (H = 192.52, p < 0.05). The same occurs with other hashtag usage (H = 98.33, p < 0.05). Therefore, these results corroborate H4. For more details, see Tables 7 and 8.
There are significant differences in the different connective actions analyzed and message formats, particularly for the actions of retweeting (H = 142.21, p < 0.05), citing tweets (H = 103.39, p < 0.05), liking (H = 199.79, p < 0.05), commenting (H = 143.05, p < 0.05), and replying to comments (H = 109.29, p < 0.05). In addition, there are significant differences in the different connective actions analyzed and other hashtag usage (for the actions of retweeting H = 68.07, p < 0.05; citing tweets H = 57.17, p < 0.05; liking H = 104.46, p < 0.05; commenting H = 77.55, p < 0.05; and replying to comments H = 68.11, p < 0.05).
With respect to message format, the rank analysis shows that in most cases, those messages comprising “text and video” and “text and image” generate more online engagement than the other message format possibilities. With respect to other hashtag usage, the rank analysis indicates that in most cases, those messages containing hashtags on topics “not related to sustainability and related to COVID-19/digital strikes” and those containing just hashtags “related to COVID-19/digital strikes” generate more engagement and connective actions than the other hashtag usage categories analyzed. For more details about different categories, mean rank analysis results are shown in Figures 7 and 8.
Message format mean rank analysis.
Other hashtags usage mean rank analysis.
Discussion and conclusion
FFF raises social awareness about taking action against climate change, which is the 13 Sustainable Development Goals established in the 2030 Agenda (United Nations [UN], 2019). In line with Connective Action Theory, the evolution of this movement from the local to the transnational scale was facilitated by the effects of disruptive social media virality (Hopke & Paris, 2022). This technological agent enables individuals or loosely tied networks to engage with the protest of social movements.
Our research expands the understanding of the connective action analyzing how to foster people to engage with climate change via hashtag activism on Twitter. In particular, depending on who (sender and influencer types), what (message communication functions or content type), when (posting day and posting time), and how (content format and other hashtag usage), different levels of online engagement are generated via retweets, cited tweets, likes, comments, and replies to comments in the digitally networked action toward climate change, which has interesting implications for theory and practice.
From the academic perspective, this study makes theoretical contributions to the field of Connective Action Theory and highlights the need for more knowledge on message design that help to make activism discourse more effective. These findings support the notion that who sends the message is a relevant characteristic to engage people in hashtag activism (Cheng et al., 2024; Wang & Zhou, 2021). This fact evidence that this occurs not only in social protests and in the action of sharing information (Mirbabaie et al., 2021) but also in environmental protests and to encourage other connective actions, such as citing, liking, commenting, and replying to comments.
Although contemporary social movements are highly decentralized, previous research posit that protest leadership remains crucial in claim-making and dissemination in the digital sphere (Cheng et al., 2024; Mede & Schroeder, 2024). In this sense, our findings add that icon-influencers in the environmental activist community, like Greta Thunberg and NGOs, are key drivers to incite people to engage with FFF by means of different online connective actions (citing, liking, commenting, and replying to comments).
Truly, Greta Thunberg became an “influencer” thanks to social media, so her “example” evidences the power of social media to give a visible and powerful voice to a “regular” young girl. In this sense, findings also show that other types of senders can be important “activists” to engine connective actions (Mirbabaie et al., 2021), and more specifically, results suggest that regular citizens can play a crucial role in fostering online conversations (replying to comments). Hence, regular citizens can be part of the solution on the call for more knowledge on how to sustain the “debate” of the protest over time (Mede & Schroeder, 2024).
Regarding the question of what, previous research highlights the importance of employing strategies to ensure that the content of the message should be consistent across the different platforms used in connective action movements (Lukito et al., 2023). However, others posit that not all contents of the messages are useful to enact connective actions (Clark-Parsons, 2021; Mirbabaie et al., 2021; Shahin et al., 2021). This article adds to this literature that, in the case of climate change protest, people may seem to be more participative (citing, liking, commenting and replying to comments) to those participants in the network that try to overshadow the legitimacy of the movement. In addition, findings show that people actively participate in the FFF networks with messages to take action and expressly join climate strikes online (due to the COVID-19 lockdowns), as well as to manifest the COVID-19 pandemic situation as a consequence of climate change, which suggest that social media, as an organizing agent, becomes even more important during crisis situations.
In addition, regarding the question of when, this study introduces new insights on the importance of the posting day and time to bear in mind to make people engage with a social movement’s digital action. Therefore, while previous investigations have posited that activity and interactions that occur on connective social movements vary over time (Cheng et al., 2024; Mirbabaie et al., 2021), our results add that the posting time is also another message characteristic that helps to explain how varies such online activity over the hours of a day as well as during days of weeks. In this sense, the findings point out that people in favor of climate change protest address their commitment not in their leisure time, but during the week and in their working hours, albeit these findings are relevant for the connective actions of retweeting, citing tweets, and commenting tweets containing #fridaysforfuture.
The format or how the message is presented is another message characteristic to consider. The results of this study may support the argument that social media enables individuals to use creative formats in their posts that help to expand participation and levels of commitment and action to a social movement (Shahin et al., 2021; Uwalaka & Nwala, 2023). In addition, as occurs in social protests (Mirbabaie et al., 2021), the combination of “text and video” and “text and image” fosters people’s engagement with digitally networked action. This study also finds new and relevant combination of formats, which are that the use of diverse hashtags related to the protest, as well as others related to issues that matter to society on a global scale, like the COVID-19 emergency situation, is an effective tool for attracting attention to social movement networks.
From the practical perspective, and based on the example of FFF, several suggestions could be proposed to sustain and foster users’ engagement with the digitally networked action of social movements. First, icon-influencers of the movement should actively participate in their social media accounts, as they truly have an impact on other individuals’ engagement with social causes. Second, individuals tend to be more willing to connect with messages oriented toward calling for actions and mobilizations. Third, the time when a post is sent could also matter, and it should be taken into consideration that people are connected to social media movements and are willing to participate during their working hours. Fourth, the commitment of people to social movement networks should also depend on the format of the message. In this sense, the use of videos and image is highly recommended, as well as other hashtags for actions related to protests (e.g. digital strike) and for issues that concern society at a global level. The nature of social movements strongly depends on “the voice of the people,” and, nowadays, there is no doubt that social media platforms are the most used communication method for connecting people. Therefore, as an overall contribution, the findings of this study may help to improve activists’ discursive strategies in this respect. In addition, these results, in general, can help different social movements to reinforce their digitally networked action through social media message design, bearing in mind that the commitment, loyalty, and support of “people” are needed in any social cause.
Limitations and future research streams
The current study is not without limitations. With respect to threats to external validity of this research, Twitter and FFF is the only platform and social movement selected to collect data and test hypothesis proposed. Hence, widening this analysis to other social movements and social media platforms would be advisable. Moreover, the present study utilized manual coding to collect data, whereas future research could perform an automatic completion and classification of message content types (of posts and comments to posts) using artificial intelligence algorithms. In this line, this article analyzes the content types of messages, yet comment content still needs to be investigated to obtain a comprehensive perspective of online engagement. The present study analyzes online connective actions to the FFF movement, and future research could explore whether content published on social media is helping to change people’s attitudes toward the problem of climate change.
Footnotes
Author contributions
All authors have contributed equally.
Data availability statement
Deposited data available here: Estrella-Ramón, A., Gálvez-Rodríguez, M. del M., & Serrada-Lores, S. (2024). Dataset of Tweets for the paper: “Hashtag activism on Twitter: The effects of who, what, when and how a tweet is sent for promoting citizens’ engagement with climate change” [Data set]. Zenodo. 
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Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.