Authors:
(1) Utkucan Balci, Binghamton University, United States;
(2) Michael Serivianos, University of Cyprus Technology, Cyprus;
(3) Jeremy Blackburn, University of Binghamton, United States.
Links table
Abstract and 1 introduction
2 background and relevant work
3 data
3.1 Determine Tankie Subreddits
3.2 Determination of sub -ideology and 3.3 groups yet
4 User base analysis and 4.1 Create a graph and community detection
4.2 Community growth
4.3 The user’s deportation over time
5 content analysis and 5.1 What are the tanks talking about?
5.2 Who talks about tanks?
5.3 Disturbance analysis
5.4 toxic analysis
5.5 field analysis
5.6 LEMMYGRAD analysis
6 discussion and conclusion and 6.1 restrictions
6.2 Antiquities, future work and references
Data
B name is entities
C Disable Analysis
Domain analysis d
C Disable Analysis
As mentioned in Section 5.3, we perform a qualitative analysis on a small scale using a sample of publications (20 of each society for each interpretation) that contains non -calculated/conceptual pairs in theory to inform our interpretations. To increase the health of our conclusions, we also implement the quantitative verification experience using acute toxicity
The model from API perspective. These experiments aim to verify the validity of our interpretation of the difference between the pairs of words related to the following: 1) Acceptance of the accounts of the Chinese Communist Party (CCP), 2) The Stalinist Coalition, 3) accepting Russian accounts in Ukraine, and 4) The hostile tendency of the Azas.
In our analyzes, we assemble the spouses of heterogeneous/conceptual words for each society. For example, to verify the validity of our findings about the anti -Zionist tendencies, we analyze the posts that contain “Zionist”, “ISNTREAL”, “Zionists” and “Zionist” the keywords of the tank community, as well as the wrong words corresponding to other societies that we analyze. However, in cases where keywords have polarized or different meanings, we divide them into specific interpretations within certain societies (for example, when checking the health of Stalinism from the tanks, we do not put “Khrushchev” and “Stalin” in the same keyword list). Our explanations can be seen with the keywords used for each community of Table 10.
We do not verify the validity of the results we have reached on the editorial terms of ideologies because we find that the tanks are the most toxic society among the societies that we analyze (see Section 5.4). Likewise, we do not verify the authenticity of the results related to tanks that tend to the media sponsored by the state, as our results reveal that the tanks have the highest percentage of users who share the media from the “global audit forces”, which are generally known to be sponsored by the state (see Section 5.5). We also do not do more analysis regarding American policy, because the imbalance between tanks and/R/democracy is the only great observation in our data.
C.1 Check Health
Our analysis indicates the posts that were taken (20 for each society and interpretation) that the tanks often support CCP, especially compared to other left societies. We find many publications that show support for CCP and blame the West for CCP-for example:
The media is forced to target CPC, which often leads to its distortion.
During our analysis, we face leaflets that deny the genocide of each society with varying frequencies, while the tanks primarily deny the occurrence of genocide – for example:
For me, internal schools work as potential terrorists schools, and China’s approach appears to be more humane than the United States.
We also confirm that the tanks are often used “rioters” to identify demonstrators in Hong Kong/Tiananmen Midan – for example:
Hong Kong riots are Psychoan Frickin.
and,
I will not conflict with the Tiananmen Square massacre. The peace soldiers who died, addressed the disturbances fed by the CIA.
We find tanks talking negatively about Trotskin and the abolition of fading-eg:
Khrushchev was a big fool when it was about fading.
However, we notice the mixed functions related to the scratching. This can be attributed to the fact that although tanks often oppose the removal of bullets and criticize Khrushchev on this basis, they also show sympathy for him as a former leader of the Soviet Union who headed the Soviet invasion of Hungary. We also find that R/Democrats use “Tankie” as a verbal term and show opposition to this society
In our eyes, we find many publications of tanks that express their support for the Russian invasion of Donbass – for example:
DPR and LPR protection from NATO NATO are positive.
In our analysis of the jobs that were taken from other societies, we notice a mixture of content. It is worth noting that R/Communism and R/Socialism show a higher frequency of jobs that express Russia’s support compared to R/anarchism. Moreover, our analysis reveals that the majority of the leaflets from which samples were taken from the tanks that mention the opposition of Zelensky Expression for him – for example:
Zelensky must have the Azov icon on his head LMAO.
We also see that the leaflets from which samples were taken of tanks are often hostile to Zionism-for example:
Zionism equals fascism.
and
This is Isntreal and Nah, we do not support Israel.
We note many jobs that express the opposition of Israeli or Israeli policies through other societies. However, R/Democracy shows the slightest frequency of these functions compared to other societies.
C.2 quantitative verification
To verify our explanations quantitatively, we first benefit from the Extivity_toxicity model from the perspective of an application programming interface. Then we compare the high toxicity levels of the various wrong keywords for each interpretation. Table 10 shows the basic statistics and similarities of tens of high toxicity for the main words that indicate their imbalance.
Accept CCP narration. Our analysis reveals that the tanks show the lowest percentage of the high acute toxicity of publications that contain the “CPC” keyword in comparison with the publications of other societies that contain the keyword “CCP”. On the contrary, the tanks offer a higher level of high degrees to the main words related to the Uyghur group genocide. Based on our samples data, we conclude that the tanks tend to adopt a more toxic tone when depriving the genocide of Uyghur, while other societies are involved in a less toxic speech when discussing the topics related to Uyghur. Moreover, we note that R/Communism and R/Socialism show a low part of high toxicity when processing “camps”, which are often associated with the concentration camps created by CCP or Nazis. Finally, we find that tanks have a higher percentage of high degrees when mentioning “rioters” (which may be towards demonstrators in Hong Kong) compared to the participation of other societies that mention “demonstrators/demonstrators”.
We find that the tanks have the second highest percentage of high acute toxicity for their posts that contain Tiananmen box compared to the participation of other societies that contain “riots”.
Stalini tends. We find that the tanks display the highest percentage of high acute grades in the posts that are characterized by the main words hostile to the stalemate or not related to vanishing compared to R/Communism, R/Socialism, R/Anarchism. Moreover, we notice more comparable ratios when comparing the keywords used by the tanks with Stalinist keywords or supporting the Assr in R/Socialism and R/Anarchism. In addition, we determine a similar percentage of high degrees in the use of R/Democrats for tanks, which increases the negative feelings of tanks towards anti -receipt and removing fading.
Acceptance of the Russian narration on Ukraine. We find that the tanks show the second highest number of high acute degrees in toxicity for functions with the keywords related to the Donbas region in Ukraine. However, less than 1 % of Tankie posts show high degrees, which may be due to their support for self -declared republics in Donbass. Moreover, the tanks have more than four times a higher percentage of high degrees of functions that contain “Zelensky” compared to R/democracy posts containing “Trump”. This result is an additional indicator to align the tanks with the Russian narration.
The anti -Zionist tendency. Our analysis reveals that more than 5 % of Tankie posts containing major words associated with zionismraated appear high degrees of toxicity, which is the highest percentage compared to other societies. Interestingly, the tanks offer a greater percentage of high degrees of jobs that feature the main words related to Zionism from their own use of the term “ISNTREAL”.
