Exploring Genocide Discourse on YouTube: A Case Study of the Israel - Hamas War

Mila Georgieva, Valerie Cortés, Shiyun Qian, Talida Munteanu, Steven Delmotte

Introduction

Over the last decade, social media has evolved into a powerful force, playing a pivotal role in shaping public opinions and influencing discussions across a wide range of topics. Among these digital platforms, YouTube stands out as a preeminent video-sharing platform, registering no more or less than a billion hours of daily content consumption by users worldwide (Dean 2023). The spectrum of content creators on YouTube, as highlighted by Rieder et al. (2022), is remarkably diverse, encompassing “amateurs engaging in intimate sharing of their everyday experiences, to star YouTubers with millions of subscribers, to established television networks and music labels that use the platform to distribute their content to mass audiences, and in particular younger viewers” (Rieder et al. 2022, p. 2). Hence, we now assist in the phenomenon of micro-celebrity (Lewis 2020), where strong voices can influence their followers’ opinions and reshape their perspectives, feeding them with information or entertainment.

As through the medium of audiovisual communication users engage in the creation and dissemination of content, regardless of their level of expertise, divergent opinions are polarized on platforms like YouTube. This participatory digital landscape usually comes with its challenges. Extensive research has illuminated the prevalence of extreme political content (Ribeiro et al. 2020) and the propagation of misinformation (Bounegru et al. 2020) on YouTube. Ha et al. (2022) have gone a step further, characterizing the platform as a fertile ground for the germination of conspiracy theories. When it comes to mainstream media, Glaesener (2023) raises the concern of their dominance on YouTube when investigating the German YouTube sources of information on the Russia-Ukraine war. Hence, in his paper, Glaesener (2023) highlights that understanding the influence of mainstream media on the platform is crucial, posing the question of whether YouTube’s content is dominated by mainstream media or diversified through channels independent of traditional media.

In the context of the October 7 attacks by Hamas, followed by Israel’s response, a plethora of controversies have been created among social media users, whose discourse has taken different contours. Besides this, TikTok has faced allegations of influencing young minds regarding Gaza, as stated by Malik (2023), while Palestinians have claimed that their content is not being promoted on social media platforms (Siddiqui et al. 2023). Hence, we aimed to understand how content is being displayed on YouTube mainstream media, which informs users about the Hamas-Israel war, and how commenters react to YouTube videos on the topic of genocide.

Considering these aspects, our research embarks on an exploration of the discourse on YouTube, with a specific focus on the nuanced and complex topic of genocide within the context of the Israel-Hamas war. Following Glaesener’s study (2023), we aimed to investigate the dynamics of content dissemination, urging researchers to delve into source diversity for a comprehensive understanding of the digital landscape, along with how discourse is created around the genocide. To illuminate this landscape, we analyze search results from specific queries, including “genocide”, “Gaza genocide”, “Jewish genocide”, and “October 7 genocide”, during discrete periods spanning October, November, and December. By scrutinizing these queries, our research aims to not only uncover prevailing thematic structures but also to discern patterns in the evolution of content over time.

Drawing on insights from Rieder et al.’s (2023) exploration of YouTube’s influence on political opinions, our research seeks to challenge prevailing assumptions. The conventional wisdom of YouTube’s Western-centric dominance in political discourse is subjected to scrutiny. Acknowledging the complexity of opinions within the digital realm, our paper adopts a digital methods approach (Rogers 2019), enabling us to uncover thematic structures, scrutinize the most connected video network, and trace the evolution of discourse from a user’s perspective.

Research Questions

Considering the previous section, our research paper aims to answer three main questions.

• RQ 1: What are the predominant topics identified within the videos between October 7 - December 14?
• RQ 2: What type of information clusters could be found within the video network?
• RQ 3: How do the comment sections of the top 3 videos for this period inform us about the discourse on the war?

Methodology

The first stage of our data collection process started using YouTube Data Tools (Rieder 2015) to gather a video list for all four queries in different periods. Then, we downloaded the video transcripts for each dataset. In total, we collected 1.997 video transcripts, some of them were in French, Hindi, Spanish, and Hebrew but they were translated into English to conduct thematic analysis. We constructed a dataset for each query per month and uploaded them into 4CAT (Peeters & Hagen 2018) to tokenize the transcripts and remove stopwords or emojis. This part of our methodology was inspired by the one used by Shekhar & Saini (2021) in their research using topic modeling. We started with the data scraping step and moved into the data cleaning process, both automated by the tools we used (Youtube Data Tools and 4CAT).

The next step was exploratory data analysis “to understand better the main features of data, variables, and relationships that hold them” (Shekhar & Saini 2021). Thus, we exported and analyzed the most frequent bigrams and words for each data set and analyzed them.

During this process, we encountered similar findings in all 12 data sets (each query had 3 different datasets based on timestamp), meaning that there were no significant changes, thematically speaking, during the three months for each query. Instead, we identified more general topics that were dominant through all datasets during the three months. Based on this preliminary finding, we restructured our data corpus and merged all transcripts into one single text (214.290 characters). One of our challenges was that ChatGPT 3.5 in its free version has a limit of characters to process and our corpus surpassed that limit. Thus, we uploaded it into 4CAT and extracted a list of bigrams with their frequency. Then, we analyzed the most frequent bigrams and processed 300 of them using an AI tool (ChatGPT 3.5.), providing the instruction to use Latent Dirichlet Allocation (LDA) (Blei et. al. 2001) as the topic modeling algorithm to select five topics from the bigrams. The number of topics was randomly selected after doing a qualitative analysis ourselves and finding six general topics. The prompt we used with GPT goes as follows:

[You [GPT 3.5] are a topic modeling expert. Prompt: Using Latent Dirichlet Allocation algorithm, you are going to (1) find six dominant topics from the following bigrams (2) provide a name for each topic.
[header word_1 word_2 value]
[list of bigrams]

To identify the information clusters within our data, using YouTube Data Tools (Rieder 2015), we downloaded a co-commenting network of all four queries. The result was a network with 1.709 videos (nodes) and 44.942 edges linked based on the users’ commenting patterns. For this step, we used Gephi to visualize the network, filter the clusters, and identify different user communities. Then, we implemented a qualitative analysis of the most viewed and commented videos in the network to find how these videos are connected and how users engage with the videos they commented on.

For the final direction of analysis, the top 4.000 comments for each of the top three videos (most viewed and commented ones) were analyzed, first extracting them with YouTube Data Tools’ Video Comments module (Rieder 2015). Later on, those comments were explored using 4CAT’s word tree module as well as the Jason Davies Word Tree website (Wattenberg and Viégas 2008). As already existing work on the relevance of word trees shows, this "visualization and information-retrieval technique [...] enables rapid querying and exploration of bodies of text" (Wattenberg and Viégas 2008). Therefore, in the context of our research paper, it allows us to identify and visually present the wider narratives and patterns within the comment sections of the videos. Since the number of comments in each section is above 28K, each sample of 4000 comments is not a fully representative sample, thus one of the limitations of this analytical approach. Finally, the presented Word Tree in this paper (Fig. 1), highlights an even more filtered selection from all 3 videos’ comment sections, serving only as a template for understanding the process of assembling the word tree analysis and the corresponding findings. The comments in this “template” were selected manually, based on the already existing observations of the research process, therefore narrowing down the overall representativeness of the vast amount of comments even more. As shown in Figure 4, the main keywords used as “root words” in all three cases were “Genocide”, “Israel”, “Palestine”, and “Hamas”. The keywords were identified with the help of 4CAT’s processors and further manual exploration of the datasets, with a final goal of extracting information that is relevant to the context of “Genocide”.

Fig.1. Word tree template for understanding the findings from the comment sections.

Findings

The results reveal three major findings. First, contrary to our expectations, there is no significant development in the discourse on genocide in the context of the Israel-Hamas war. Instead, contextualizing the four queries leads to relatively similar search results. For the video transcripts, we found that the most frequent bigrams for the four queries were similar throughout the three months of analysis. With the bigrams from our data corpus (all transcripts merged), we identified manually six topics that were predominantly and compared them with the ones delivered by GPT3.5, as seen in Fig. 2. Comparatively, we found that two out of five topics (Israel-Palestine conflict and political issues/international relations) are similar in keywords and the remaining three were clustered by GPT into even border categories than the ones we identified.

Fig.2. Comparison of topics identified within 300 most frequent bigrams.

Additionally, as shown in Fig.3, Gaza is the most paired word in the top 30 bigrams, it is connected with words around the conflict itself (bombing, Israel, war, strip) and population impact (food, people, Palestinians). The lack of other visible frequent pairings can be due to the extension of our transcript corpus that allowed different semantic versions for similar words (e.g. support, supported, supports).

Likewise, in all three months, the same three videos were the most viewed and commented on. Thus, our second major finding is that while most videos in our dataset come from official media organization channels, such as Fox News, AJ Jazzeera English, and NBC News, the most viewed and commented ones are by individual content creators [e.g. the channel of Priya Jain, creating educational content, tailored for India (Jain 2018); Last Week Tonight’s channel - a “news satire television program hosted by comedian John Oliver” (“Last Week Tonight with John Oliver” 2024), and the TV show Piers Morgan Uncensored (Morgan 2021).

When it comes to the findings from the three comment sections of the most viewed and commented videos, we see that Priya Jain has the biggest diversity in terms of polarized opinions and engagement in the comment section, also considering their number - more than 94K. Here, the topic of genocide is understood through self-identification and references to other historical events, such as being “Kashmiri Hindus” as a predisposition to support Israel, or the “Sikh community in 1984”, the “Mappilah riot”, and “Bangladesh Liberation War” as reasons to support or condemn the discussed genocide. There is a strongly expressed support for either Palestine or Israel, communicated through the national belonging of Indians, in comments such as “i am indian i support palestine” or “indians are with israel”. This generalization of the statements is the prevalent form of commenting on this video. The most apparent connection to the topic of genocide, however, develops around three other terms - “Israel”, “Hamas”, and “Terrorism”. A very strong critique goes in the direction of Israel in comments like “israel is right but rapping women…” and the overall frustration with the violence and actions against humanity as “hamas is terrorist yes or cowards who kill women", “hamas and islam threat to humanity”, “hamas terrorists killed jewish children”.

Fig.3. Matrix plot made with top 30 bigrams, using RAW Graphs 2.0.

These comments also seem to provoke a backlash of opinions on whether the “defense actions of Hamas” are a synonym of terrorism, resulting in claims such as “hamas are terrorist and arab countries are terrorist organizations”, “hamas is terrorist and supported by russia” or “[...] controlled by jihadist iran”, “hamas terrorists are not fighting against israel but against the jewish”.

Moving to Last Week Tonight’s comments, we find a drastic change in the “temperature” of claims against Israel, however, the comments are rather anti-genocide and pro-humanity targeted, rather than expressing support for Palestine specifically. The examples point to Israel as “rooted in grave immorality”, being “extremist” and having a “colonial satellite”. There is an expanded palette of understandings of what genocide is, often found in the same context as “apartheid”, “basic racism”, “terrorism and expulsion of innocent”, “ethnic cleansing”, and “colonialism”. Furthermore, we also identify the development of the discourse by noticing the repetition of the word “Gazans” as a recurring way to talk about “military dictatorship” or the murder of children and women.

The third video that we analyzed was a debate on the Israel-Palestine War hosted and posted on YouTube by Piers Morgan Uncensored. The discussions created in the comment section encapsulate strong sentiments of support and solidarity for the Palestinian cause, emphasizing human rights, peace, and a collective call to cease what is strongly condemned as genocide. Linked to Palestine, we identify syntagms such as “Human rights”; “peace” and “humanity”. Furthermore, reference is made to historical atrocities, such as the Assyrian and Armenian genocides, drawing parallels to the present-day crisis: “they were treated as a loose ethic group with no fixed territory”; “armenian genocide and that of the greeks hundreads of thousands of assyrians lost their lives in racially and religiously motivated atrocities”. The dialogue seems to amplify discussions on the broader context of global events, including mentions of China and Ukraine, hinting at a wide-ranging exploration of contemporary geopolitical issues: “china, ukraine and now palestine but what is the actual definition of genocide”. When it comes to “Hamas”, the discourse is formulated around the impact on the Palestinian civilians: “Devastating human suffering”; “Civilian suffering”; “ethical considerations”, as well as on the actions required to stop the war: “Diplomatic solutions”; “Urgent calls for an immediate ceasefire”; “Stop genocide in Gaza”; “Free Palestine, Free Gaza”.

Furthermore, the conversation extends beyond mere critique, delving into the intricacies of international and regional politics. Criticisms are directed towards Israeli policies, with specific attention to the limitations imposed on the movement of essentials into Gaza and accusations of committing genocide: “Severely limited the movement of food and water, fuel, medicine and other essentials into gaza”; “Monthlong ground and air war has killed more than palestinians [...] enclaved”; “Commiting the crime of genocide against Palestinians in Gaza”. Moreover, in relation to Israel there have been created debates on the topic of terrorism and violence: “What can we do to stop the genocide of the palestinians”; “The assyrian genocide, a fate worse than death”. Politics have also been brought into discussion: “Demands a diplomatic solution that addresses the root causes and aspirations of both parties”; “the israel hamas conflict is grounded in the stark reality of civilian suffering”. The reluctance of certain House Democrats to support a resolution for a ceasefire further underscores the complexity of political dynamics. Hence, we identify phrases such as “demanding from leaders in Washington to stop Israel’s genocide” and “ceasefire protest in Washington”.

Amidst the condemnations, there is a call for urgent diplomatic solutions and humanitarian actions to address the root causes of the conflicts and prevent further human suffering. Overall, the discourse captures a blend of advocacy, critique, and a fervent call for a global response to alleviate the plight of those affected by the ongoing crises.

Moving to the co-commenting network analysis, as mentioned in the methodology part, we used YouTube Data Tools (Rieder 2015) to download the co-commenting network of all four queries and visualize the network with Gephi. Applying the ForceAtlas2 layout algorithm and preventing overlap alternatives, we got a graph with 1.709 nodes (videos) and 44.942 edges. These videos belong to 1.042 different YouTube channels, including Fox News, AI-Jazeera English, Last Week Tonight, and Sky News.

Previous studies have already demonstrated the significance of analyzing source diversity and type of information. According to Glaesener and Tim (2023), there is always tension between mainstream media and alternative media on YouTube. Although YouTube has been regarded as a benchmark for participatory culture since 2005, some scholars also considered it merely as “another outlet for mainstream media”. As the “critical content provider”, YouTube significantly influences the public discourse (Glaesener & Tim 2023). Therefore, we need to explore the source diversity regarding the Israel-Hamas war. Does mainstream media shape the public discourse on YouTube? Or is it the alternative media/independent content creators moderating audiences’ opinions more?

Thus, we manually classified some significant main channels based on their media types: Western mainstream media, non-West mainstream media, Western independent content creators, and non-West independent content creators (Fig.4). From the chart, we can see that the numbers of western mainstream media are far more than non-west mainstream media. Among all the 1.042 YouTube channels, only AI-Jazeera English, AJ+, Middle East Eye, and Islam Channel are the Arab mainstream media. Other Arab media channels are either not qualified to be mainstream media or are independent content creators (e.g. Monkeyshines1 and Islamispeace). Moreover, we highlighted the Top 15 most commented videos in yellow in the chart. The top 3 most commented videos all come from content creators: Priya Jain (94.641 comments), Piers Morgan Uncensored (61.079 comments), and Piers Morgan Uncensored (55.902 comments). Of all the top 15 videos, 9 of them were published by content creators. From this, we can see that while most videos in our dataset come from official media organization channels, the most viewed and commented ones still are by individual content creators.

Fig.4. Classify main channels in co-commenting network based on media types

For the co-commenting network analysis, due to a large number of videos, we chose to analyze only the top 15 videos with the most comments (Fig.5). In the network, each node is a video and is connected with others if one or more users commented on them. The size of the node is based on the view count. The bigger the node, the more views the video has. The thickness of the edges represents the strength of the connection between these videos. If nodes are the same color, they were published by the same YouTube channel. Within this network, we try to identify different information clusters, find out how these videos are connected, and how commenters engage with the videos they comment on.

Fig.5. The Top 15 most-commented videos in the co-commenting network, using Gephi.

The node (video) in blue is from the channel of Priya Jain, with the title of “INDIA will support ISRAEL for.…🇮🇳🤝🇮🇱”. As the most commented video, it is connected with three other channels: Middle East Eye, TRT World, and Johnny Harris. As mentioned in the previous part, Priya Jain’s video itself is pro-Israel. However, its comment section has polarized opinions — commenters use generalization statements to support Israel or Palestine, such as “I am Indian, I support Palestine” or “Indians are with Israel”. What is more interesting is that of all three videos connected with Pirya Jain, two are supportive of palestine. One of them is “Why People are Siding with Palestine” by Johnny Harris, an American independent journalist with 4.82M subscribers. In this video, Johnny explained the difference between supporting Palestine and supporting Hamas, arguing that the terrorist attacks of Hamas should not be conflated with the legitimate liberation movement of Palestinians who only want freedom, dignity, and autonomy. The other video is “Don’t be scared father” - A moment between a Palestinian boy and his father in Gaza hospital by Middle East Eye, which portrayed a heartbreaking moment of a Palestinian man and his child comforting each other after being injured in the attack. Commenters expressed support for Palestine in the comments section of both videos, such as: “Palestinians have the right to resist and fight back against Israel.” and “Palestinian children’s are very well raised, super strong”.

The four nodes in yellow (videos) are all from the channel of Piers Morgan Uncensored. These four videos all connected, indicating that Piers Morgan’s channel has high audience loyalty and engagement. In addition, these four videos are linked to the other two videos from Fox News and PowerfulJRE as well. The Fox News one is “HEATED DEBATE: Cornel West, Alan Dershowitz spar over Israel-Hamas war”. Similar to the form of Piers Morgan’s video, the Fox News one is also a debate between two hosts, Cornel West and Alan Dershowitz. The PowerfulJRE one is Freaking Out Over the Israel and Hamas Conflict, although the format of this video is an interview rather than a debate, I believe that the similar program format is the reason why these six videos are linked to each other and why users co-comment on each other.

The cyan node (video) on the upper right corner of the network is “Children mercilessly killed by Hamas in Israel massacre - as Gaza is pummelled” by Channel 4 News, which is reported by Secunder Kermani to portray the tragic scenes in Kfar Azak Kibbutz and Ashkelon after the Hamas terrorist attacks. This video is connected to eight other videos from different channels: The Young Turks, Fox News, Sky News, Piers Morgan Uncensored, Johnny Harris, travelingisrael.com, NBC News, and WSJ News. Interestingly, this co-commented cluster connected both mainstream media and independent content creators. While the video itself is supportive of Israel, the co-commented videos it connected are both supportive of Israel and supportive of Palestine.

Discussion

First, as observed, by analyzing the transcript of the videos, our initial queries did not alter the topics we found. In fact, contrary to our hypothesis, broader and general topics around the Israel-Palestine war such as human rights, the October 7th attack, and international politics were the most dominant through all dates. This may be influenced by different factors. One, we observed that the most popular videos were the same ones during all queries, which would have caused the transcripts of those videos to be present in all data sets, and when merging the transcripts, their content was repeated, making them more relevant for the topic modeling algorithm. Two, as mentioned above, those videos did not replicate radicalized discourses and in most of them, their content was focused on providing contexts for the conflict. These findings complement and differ from other investigations on conflict and YouTube, in which the authors found the content of war-related videos reinforced new forms of “public diplomacy” (Christensen 2008) and positive sentiments toward armed forces (Crilley & Chatterje-Doody 2020).

When looking at the findings in terms of how the comment sections inform us about the war, we see how different interpretations and understandings of genocide and humanity are transmitted in history and through different lifetimes, thus making “genocide” a topic rather hard to define the borders of. Therefore, features like the comment section of YouTube become a meaning-making unit of large-scale perspectives. The findings also support the idea of YouTube as a platform hosting an “increasingly participatory media culture” (Arthurs et al. 2018), considering that the top viewed and commented videos for the three periods diverge from the form of official news channels, and therefore host more diversified opinions, based on cultural and national belonging, strongly expressed condemnation of violence, and bring a spectrum of perspectives on what “genocide” and “humanity” should be. Next, zooming into the three comment sections, we see the interplay between “issue and platform vernaculars” (Rieder et al. 2018). In support of the authors’ findings (2018), it is not only the issue at stake that matters for the video’s engagement rates, but also the strategic presentation and promotion of the content. In the case of Priya Jain and Last Week Tonight, for example, we see the highest number of interactions under a YouTube short format, as well as a news satire style of content that nevertheless provokes more clearly expressed assessments of “genocide” and critical reactions to the parties involved. At the same time, Piers Morgan Uncensored video leaves room for discussion in the comment section too, due to its debate format, ranging from strong support for one side to critiques of actions, policies, and the humanitarian impact of the conflict. While genocide is condemned, the call for diplomatic solutions and global intervention constitutes the predominant topic of discussion, as Israel’s response seems to be more criticized than in any other comment section.

Conclusions

Throughout this research, we applied three different methodological approaches to understand the discourses on videos related to genocide in the context of the Israel-Palestine conflict and in their comments sections. By analyzing the video’s transcripts, we discovered, contrary to our initial hypothesis, that genocide queries result into videos which content is predominantly focused on general topics around the conflict such as international politics, government policies, and human rights, probably the product of platform mediation and focus on select “which channels provide expert, authoritative and reliable information” (YouTube 2023). These findings contrast with our analysis on the comment section of the most popular videos, where we encountered more political discourses expressed by users, in which comparisons with other armed conflicts are often found. Further investigations can explore how analyzing videos’ transcripts using LLMs may diversify researchers’ insights on qualitative methods. Likewise, comments sections on YouTube remain a suitable source — even more diverse than the actual videos’ transcripts in our case study — to track communities and discourses in controversial topics.

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-- Main.BernRieder - 14 Feb 2024