How do tanks disrupt online political narratives

Connection table

Summary and 1 Introduction

2 Background and related work

3 data

3.1 Definition of Tankie subtitles

3.2 Defining Ideology Sub -Series and 3.3 Post Collection

4 user base analysis and 4.1 graphic structure and community detection

4.2 Community Growth

4.3 User transitions over time

5 Content Analysis and 5.1 What are the tanks talking about?

5.2 Who are the witnesses talking about?

5.3 False alignment analysis

5.4 toxicity analysis

5.5 Impact Analysis

5.6 Lemmygrad Analysis

6 DISCUSSION AND CONCLUSION AND 6.1 LIMITING

6.2 Inferences and future studies and references

A data

B Nations

C False alignment analysis

D field analysis

C False alignment analysis

As stated in Chapter 5.3, we perform a small -scale qualitative analysis that uses a sample of writing that is misled/conceptually containing homomorphic word pairs (20 for each comment 20) to inform our comments. In order to further increase the validity of our results, we also apply a quantitative verification experiment using serious_toxicity.

Model provided by perspective API. These experiments aimed at verifying the interpretation of the misallation of the word pairs about the following: 1) Acceptance of the Chinese Communist Party (CCP) narratives, 2) Stalinist bending, 3) The adoption of the Russian narratives in Ukraine and 4) anti -Zionist bending.

In our analyzes, we group the Homomorphic word pairs conceptually in the wrong alignment of each community. For example, in order to verify our findings on the anti-ionist tendencies of the tanks, we analyze the wrong alignment words for other communities we analyze as well as “Zionist”, “Isntreal”, “Zionists” and “Zionism” keywords. However, in cases where keywords have polarized or different meanings, we devote them to specific comments in certain communities (for example, while confirming the Tanks Stalinist bending, we do not put “Krushchev” and “Stalin” on the same keyword list). The categories of our comments made with the keywords used for each community can be seen from Table 10.

Since we find that the tanks are the most toxic community among the communities we analyze, we do not confirm our findings on ideologies for humiliating terms (see section 5.4). Similarly, our consequences do not confirm the findings of the tank leaning on state -backed media, it reveals that Tankies has the highest rate of users who share news organizations from “revisionist world forces”, known to be state -supported (see section 5.5). Also, we do not make any more analysis of US politics, because the only important observation in our wrong alignment data between tanks and r/democraticocialism.

C.1 qualitative verification

Our analysis on the sampled poles (20 for each community and interpretation) shows that tanks mainly support the CCP, especially compared to other remote communities. We find many posts that support the CCP and support West for their accusations.

The media is often forced to target the TBM, which leads to misleading.

During our analysis, we encounter publications that reject the Uighur genocide for every community with changing frequencies, and tanks mainly deny the formation of the genocide – for example:

In my opinion, boarding schools serve as a school for potential terrorists, and China’s approach seems more humane than the USA.

We also confirm that tanks often use “rebellion için to describe protesters of Hong Kong/Tiananmen Square – for example:

HK rebels are frikin psychos.

And,

I will not object to the massacre of Tiananmen Square; The soldiers who died by addressing the CIA fuel unrest, rest in peace.

We see that the definitions speak negatively about Trotskyists and Stalization –EG:

Krushchev was a great fool when it came to De-Stalination.

However, we observe mixed tasks about Krushchev. This can be attributed to the fact that tanks are predominantly opposed to Stalination and criticizing Krushchev on this basis, but they may be attributed to the fact that the USSR, who presided on Hungary’s Soviet invasion, as a former leader. We also see that R/Democraticism uses “tankie ası as a humiliating term and shows opposition to this community.

In our example, we find many articles from tanks that express support for invasion of Russian Donbass – for example:

The protection of DPR and LPR, financed by NATO, is a positive action.

We observe a mixture of content in analyzing messages exemplified from other communities. In particular, R/Communism and R/Socialism exhibit a higher frequency of writing that expresses support to Russia compared to R/anarchism. Moreover, our analysis is the majority of the tasks exemplified from the tanks who talk about Zelensky’s opposition to him – for example:

Zelensky must have a symbol of Azov in his head.

We also see that the exemplary messages of the tanks are predominantly anti-ionist.

Zionism is equal to fascism.

And

This Isntreal and Nah do not approve of Israel.

We observe numerous tasks that express opposition to Israel or Israeli policies in other communities. However, R/democraticism exhibits the lowest frequency of these tasks compared to other communities.

C.2 quantitative verification

To confirm our comments quantitatively, we first use the serious_toxicity model of the Perspective API. Then we compare the high levels of toxicity of various incorrect alignment keywords for each comment. Table 10 shows the basic statistics and proprotions of high serious_toxicity scores for keywords that show incorrect alignment.

Acceptance of the CCP narrative. Our analysis reveals that tanks exhibit the lowest severe_toxicity rate for poles containing the “CPC” keyword compared to the publications of other communities containing the “CCP” keyword. On the contrary, tanks exhibit a higher ratio high points for keywords related to the Uighur genocide. Based on our sampled data, while denying the tanks of the tanks, while tending to adopt a more toxic tone, other communities make less toxic discourse while discussing Uighur issues. In addition, we observe that the high rate of toxicity of R/Communism and R/Socialism is reduced when dealing with “camps olan which are mostly related to the concentration camps established by the CCP or the Nazis. Finally, we see that the tanks have a higher rate of high scores than the publications that refer to the “protesters/protesters (probably for Hong Kong protesters) (probably for Hong Kong protesters).

Compared to the fact that other communities contain “rebellions ,, we see that the grains have the second highest weight_toxicity scores for their publications containing Tiananmen Square.

Stalinist bending. Compared to the grains, R/Communism, R/Socialism and R/anarchism, we see that the highest severe_toxicity scores for publications containing anti-Stalinist or Stalination-related keywords. In addition, we observe more comparable rates when comparing the keywords used by tanks with Stalinist or pro -Prossral keywords in R/Socialism and R/anarchism. In addition, we further support the negative feelings of tanks against anti-stalinism and stalination by identifying a similar portion of the high scores of democraticism in the use of tanks.

The acceptance of the Russian narrative in Ukraine. The tan shows the second highest rate of the highest serious_toxicity scores for publications with keywords related to the Donbass region of Ukraine. However, less than 1% of Tankie publications exhibit high scores that can support the self -declared republics in Donbass. Moreover, Tankies has four times higher points higher than R/DemocraticSocialism’s publications containing “Trump” for tasks containing “Zelensky”. This finding serves as an additional indicator of the alignment of Tankies with the Russian narrative.

Anti-Zionist bending. Our analysis reveals that more than 5% of Tankie broadcasts, which contain keywords associated with Zionism, exhibit highly serious_toxicity scores, the highest rate compared to other communities. Interestingly, Tanies exhibits a higher score than the use of the term “Isnteral için for publications containing keywords related to Zionism.