Argumentation in political empowerment on I nstagram (2025)

Abstract: This paper adopts a distant reading approach to analyze political empowerment on Instagram. We focus on argument mining and content classification to uncover cooccurences between aspects of political empowerment and argument components. We develop an annotation scheme based on literature in digital political empowerment, classifying content into five primary categories along the aspects of political awareness, personal e-identity and political participation. We implement the modified toulmin scheme for argument component detection. As an example discourse, we chose the German discourses #WirSindMehr and #NieWiederIstJetzt.The upheaval was targeted against right-wing extremism and antisemitism. Political awareness emerged as the dominant category, highlighting convergent public concern against antisemitism and right-wing extremism. Claims and backings often contain statements about societal change and aim to raise consciousness.Calls for participation in offline events appear mostly in non-argumentative texts.

## introduction empowerment research has its roots in community psychology. there, it is defined as a "construct that links individual strengths and competencies, natural helping systems, and proactive behaviors to matters of social policy and social change" @xcite . it is also related to freire's theory 1970 of conscientization, which describes how critical consciousness is the first step to the ability of transforming one's status in society. next to social and political understanding, the individual experience of empowerment includes a combination of self-acceptance and the ability to play an assertive role in controlling resources and decisions in one's community, for example through citizen participation @xcite . the notion of political empowerment was introduced to overcome the potential lack of citizen participation in democracies @xcite . while there is no set definition of political empowerment, and many theoretical models address empowerment, they all emphasize the need for competence and experience to be enhanced @xcite . examples of empowerment outcomes are political participation, influence and perceived control or transfer of power between groups of society, or resource mobilization skills @xcite @xcite @xcite . researchers have examined political empowerment in the digital setting. several studies have specifically investigated the role of social networks in promoting political empowerment @xcite @xcite @xcite . building on this body of work, the present study examines political empowerment in social media. specifically, we strive to characterize typical characteristics of political empowerment using a birds-eye view. for this purpose, we perform two classifications. the first classifies political empowerment along the three aspects political awareness, political participation and e-identity, following @xcite and @xcite . the goal is to identify how aspects of political empowerment are reflected in the data, as a first step towards a quantitative sketch of the phenomenon. the second classification is an argument mining task. we detect argument components using habernal & gurevych's modified toulmin scheme 2017. finally, we want to identify cooccurences of the argument components and aspects of political empowerment. for example, do claims often express group identity towards a political stance? as an example corpus, we chose the german discourses #wirsindmehr ("we are more") and #niewiederistjetzt ("never again is now"). the upheaval was targeted against right-wing voters and took a stance against antisemitism after the attack on israel on the 7th of october 2023. we investigate instagram captions because scholars found that captions are where political issues are primarily communicated on the platform @xcite @xcite . ## related work: digital political empowerment in this study, we create annotation guidelines that cover all three aspects of political empowerment: eidentity, political participation and political awareness. importantly, we built on literature that focused on political empowerment via the internet, rather than political empowerment in an analogous setting. we refer in particular to the studies conducted by @xcite ; pirannejad and janssen (2019), as these were pivotal for further research. ## data compilation and description in the german political conversations of #wirsind-mehr and #niewiederistjetzt, a group of civilians reacted to the political shift to the right in the country, taking a stance against racism and antisemitism. formerly called "silent majority" by german newspapers (stuttgarter zeitung, accessed 01/2025), the upheaval was targeted against rightwing voters and politicians of the afd party. the upheaval was a reaction to the düsseldorfer forum, a right-wing meet-up that was planning the "remigration" of germans with migration background and refugees; and antisemitic incidences in germany after the terrorist attack of the hamas on israel @xcite . over a period of three months, a total of two million people protested across germany @xcite . we collected the data with crowdtangle in the period between 10/07/2023 and 03/31/2024 foot_0 . the search terms used were the hashtags #wirsindmehr or #niewiederistjetzt and spelling variants. the tool automatically searches for the words even without hashtags. we collected data from instagram. the dataset comprises 13469 posts with the post length being 91 words on average. the total token count is 1279585. two samples of around 1200 posts each were annotated for content and argument components. the annotation process is described in the sections 4 and 5. ## cooccurences finally, we want to identify cooccurences between argument components and aspects of political empowerment. for example, are premises typically used in a way that spreads consciousness? is the expression of group identity used to support one's claims? we visualize the cooccurences in a heatmap (see figure 1 .). the heatmap shows the relations between the argument components, premise, backing, claim, and non-argumentative text; and aspects of political empowerment. this section shows results in the cooccurences. ## discussion in this paper, we take a distant reading perspective on the discourse around the hashtags #wirsind-mehr and #niewiederistjetzt. we made use of argument component detection and performed a content classification to identify cooccurences between argument components and aspects of political empowerment. for this purpose, we designed an annotation scheme based on the literature around digital political empowerment. the content classification was performed with only five classes instead of ten. this has two reasons: firstly, the aspects of personal e-identity and political awareness building stood out more prominently. this most definitely is a result of investigating instagram captions, as platform functionalities such as surveys or requests to parties typically appear in other platform affordances such as instagram stories or private chats, and not in captions. for example, an aspect introduced by @xcite is interactive decision-making, which could happen in the "survey" button in stories. stories also contain a button for fundraising, but link to a new website. the second reason were class imbalances: it was not the case that aspects of political empowerment did not appear in the captions at all, but they appeared less than 10 times in the training data, unlike other classes which appeared between 104 and 732 times. this made it impossible to train our classifier for all classes. the decision to reduce classes to yield a clear classification result was thus a pragmatic but necessary one. for the annotation of argument components, we made use of the modified toulmin scheme @xcite . since we had big class imbalances again, we performed a multilabel classification with four classes: claim, backing, premise and non-argumentative text. to maintain class balance, we used a random sample of 300 posts from all data labeled as "non-argumentative text" (see tab.2 for count of annotated component labels). finally, we identified cooccurences of argument components and the content aspects of digital political empowerment (tab. 3). in general, "premises" and "non-argumentative text" are the most frequent argument components. claims were most frequently concerned with conscientization and societal change. according to our analysis, a typical backing contained conscientizing statements. all other aspects only appeared less than 1000 times. this might indicate that a claim about societal change might frequently be backed by a conscientizing statement. this hypothesis needs to be tested in future work on relation-based argument mining. a typical example could be: looking at the bigger picture, we can see that political awareness is the most frequent category in the corpus: conscientizing statements and statements about societal change appear most often. this is plausible, because #niewiederistjetzt is a statement against antisemitism and refers to the shoa, expressing: the shoa shoud never happen again. it is thus no surprise that users want to raise awareness for antisemitic hate and the rise of right-wing extremism in germany and europe. these concerns are frequently stated in all three components; premises, claims, and backings. one aspect of political awareness is commented on less frequently -reports from participation in offline events and calls to participate. within argument components, it is most frequently found in the class "non-argumentative text" which comprises non-argumentative texts, rebuttals, refutations. aspects of e-identity appear second most in our data. the expression of agreement or disagreement with a point of view was most often found in class "non-argumentative text" (3618 times), and appeared around 1000 times in each of the other classes. likely, users stated their approval with the stance in the hashtags #wirsindmehr or #niewiederistjetzt, but made no substantial argument. it is also probable that disapproval was expressed, as counter discourse is commonly tagged with the same hashtags. the expression of group identity appeared between 500 and 1500 times per component type, which is less than expected. one might think that the hashtag #wirsindmehr already expresses a feeling of identity; as participants are opponents of right-wing voters and belong to the former "silent majority" as expressed by the stuttgarter zeitung. potentially, this result is due to the preprocessing, as the hashtags #wirsindmehr and #niewiederist-jetzt were removed from the training data due to their frequent occourence. in this paper, political empowerment language is characterized by its aspects political awareness, political participation and e-identity. importantly, we only look at one aspect of instagram's archictecture, the caption. although the caption is where political messages are primarily communicated @xcite @xcite , we acknowledge that political empowerment should be studied in ephemeral content such as instagram stories @xcite which offer different functionalities. for a holistic approach to the analysis of empowerment in social media, a close reading approach should complement this work. political awareness has shown to be the most frequent category of political empowerment in this corpus. we believe that this could be corpusspecific, because the hashtags' topics were meant to build consciousness of antidemocratic forces in germany and europe. therefore, future work should test if this distribution also shows in other corpora of political empowerment. this work also illustrates the difficult bridge between humanities theories and applicability in machine-learning, as we had to follow a more coarse-grained approach due to practicalities of machine learning. nevertheless, we recommend the iterative process of starting with fine-grained approaches informed by extensive humanities theory. ## future work in future work, we will investigate relations between argument components. like this, we want to extract typical argument relations which would be particularly interesting for content analysis of #niewiederistjetzt and #wirsindmehr. future research could also include fact-checking of common claims, as well as experiment with argument similarity. additionally, a comparison with image texts on instagram would be fruitful. this would add insights about the use of different modalities of the platform. it could be interesting to explore whether the participatory aspect of political empowerment is conveyed through image captions. future work could expand this research to other platforms.