The Video Allegedly Showing Captured Ukrainian Soldiers Was Generated Using Artificial Intelligence

On June 9, 2026, a 59-second video was posted on X by @AdrianoValui. The video purportedly shows Ukrainian soldiers taken prisoner by Russian forces. Within four hours of being shared, the footage had been viewed more than 28,000 times, received 573 likes, and was reposted 192 times.

 

 

However, subsequent investigation revealed that the video was not authentic and had been generated using artificial intelligence technologies. The authenticity of the footage was examined using Grok, the Media Analysis, Verification, and Retrieval Group (MeVer), and HIVE Moderation.

Initial analysis conducted with Grok suggested that the video was not genuine, indicating that it had likely been generated using AI and may have been circulated for pro-Russian propaganda purposes. Similarly, the assessment carried out by MeVer identified multiple visual inconsistencies commonly associated with AI-generated content, further supporting the conclusion that the video had been synthetically produced.

The footage was subsequently analyzed using HIVE Moderation, which confirmed that it had been generated using artificial intelligence, consistent with the findings from Grok and MeVer.

 

Moreover, the visible TikTok logo in the video indicates that the content was not originally posted on X and had previously circulated on other social media platforms. A reverse image search was therefore conducted, revealing that the video was first shared on TikTok on November 4, 2025, by “liliakv.” It was later posted on Facebook on December 16, 2025, by a user named “Petruss Krsska,” and continued to circulate through reposts across TikTok and Facebook on various dates.

 

 

In conclusion, the video allegedly depicting Ukrainian soldiers captured by Russian forces was generated using artificial intelligence technologies. The fact that the footage circulated across multiple platforms for several months demonstrates how AI-generated disinformation can persist over extended periods and be repeatedly presented as authentic. Particularly during times of war and conflict, it is essential to verify the source and accuracy of visual content using reliable sources and technical detection tools.

 

If you suspect that a video, image, or audio file has been created using artificial intelligence or deepfake technology and would like free assistance in verifying its authenticity, you may send the link to the content or the file itself to allaboutdeepfake@gmail.com.

 

The Same AI-Generated Video Reposted with Different War Claims

On May 4, 2026, several news websites published reports alleging that Iran had struck a U.S. warship. However, the U.S. Central Command (CENTCOM) denied these claims and issued an official statement confirming that no such attack had occurred.

Despite this clarification, numerous social media users—primarily on X—shared videos purporting to show Iran attacking a U.S. naval vessel. One such video was posted on May 4, 2026, by the user @almohamadawi31.

Within 15 hours, the video had been viewed more than 107,000 times, reposted 543 times, and received over 1,400 likes. Subsequent analysis revealed that the footage was not authentic but had been generated using artificial intelligence. A review conducted using HIVE Moderation confirmed that the video was AI-generated.

The same AI-generated video, originally shared on May 4, 2026, was reposted on June 4, 2026, by the user @RussianArmys. In this instance, the accompanying claim alleged that Russia had launched a devastating missile attack on the U.S. aircraft carrier USS Abraham Lincoln, completely destroying the vessel and killing more than 200 personnel. The reposted video received over 107,200 views and more than 309 likes.

However, technical verification confirmed that the reposted footage was identical to the video circulated on May 4 and was entirely AI-generated. This case illustrates how the same synthetic content can be repurposed at different times and attributed to entirely different conflicts. Moreover, a review of posts from the account @RussianArmys indicates a consistent pattern of sharing unverified claims, fake news, disinformation, and AI-generated media.

In conclusion, both the video claiming that Iran attacked a U.S. warship and the video alleging a Russian attack on the USS Abraham Lincoln were generated using artificial intelligence. The repeated circulation of identical AI-generated content under different geopolitical conflicts demonstrates how easily synthetic disinformation can spread across social media platforms. Therefore, especially in the context of military conflicts and international crises, it is essential to verify visual content using reliable sources and technical detection tools.

If you suspect that a video, image, or audio file has been created using artificial intelligence or deepfake technology and would like free assistance in verifying its authenticity, you may send the link to the content or the file itself to allaboutdeepfake@gmail.com.

The Robot Dog Video That Looks Like Science Fiction Is Not AI-Generated

 

On June 3, 2026, a 32-second video was posted on X by a user named @myinvesthor. The video allegedly shows footage from a military exercise in China. It depicts four-legged, armed robotic dogs equipped with submachine guns mounted on their backs, reportedly being tested by a Chinese defense company. The accompanying post states that these robots are designed to enhance soldier safety in conflict zones and provide operational superiority through direct fire support.

 

 

At first glance, the video resembles a scene from a science fiction movie. Moreover, certain visual elements could suggest that it was generated using artificial intelligence. For this reason, its authenticity was carefully examined. The footage was analyzed using Google SynthID and HIVE Moderation, both AI-content detection tools. The results from both analyses indicated that the video contains authentic footage and was not generated using artificial intelligence. In other words, the video posted on X appears to be genuine.

The video also contains Chinese text and multiple watermarks. An examination of these elements suggests that the footage may have originated from a commercial or government-sponsored promotional event organized by a defense technology company specializing in unmanned tactical systems.

To further identify the manufacturer of the robotic systems shown in the video, individual frames were analyzed using Google’s reverse image search. The analysis revealed that the footage was first shared on April 1, 2026, by @Eng_china5 on X. It was also determined that the robots were produced by a private company operating in Shandong province, China.

In conclusion, the analysis indicates that the video contains authentic footage and was not generated using artificial intelligence. The armed robotic systems featured in the video highlight the increasing integration of autonomous and semi-autonomous technologies into military operations. In this respect, the footage provides insight into next-generation systems that may shape future conflict environments.

 

 

If you suspect that a video, image, or audio file has been created using artificial intelligence or deepfake technology and would like free assistance in verifying its authenticity, you may send the link to the content or the file itself to allaboutdeepfake@gmail.com.

The News Claiming That 119 Israeli Soldiers Were Arrested Was Generated Using Artificial Intelligence

An image posted on Facebook regarding Israel’s ground operation against Lebanon on April 9, 2026, appeared to be an image accompanying a news report.

 

 

The image was subsequently shared by numerous accounts on X and Instagram. On X in particular, a version posted by the user @Rizvana_Raza on April 10 was viewed 33,700 times, reposted 683 times, and received more than 2,000 likes.

According to the accompanying claim, 119 Israeli Army logistics personnel, along with trucks carrying ammunition and fuel, had surrendered to Hezbollah. The post described this as one of the largest logistical surrenders in recent history and asserted that Israel’s supply lines had collapsed.

However, the image is not authentic and was generated using artificial intelligence. The photograph was first analyzed using Google SynthID, which identified multiple indicators of AI generation. In particular, irregularities in the physical features of individuals depicted in the image—such as unnatural hand and facial structures—along with inconsistencies in text, logos, and background details, strongly suggested synthetic production through various AI tools.

The image was also analyzed using HIVE Moderation, which independently confirmed that it had been created using artificial intelligence.

 

 

A reverse image search further indicated that the alleged news story was not published by any recognized or reputable news organization. Consequently, it was determined that both the image and the accompanying claim, shared on Facebook on April 9 and later on X on April 10, were not authentic and had been generated using artificial intelligence.

If you suspect that a video, image, or audio file has been created using artificial intelligence or deepfake technology and would like free assistance in verifying its authenticity, you may send the link to the content or the file itself to allaboutdeepfake@gmail.com.

Video Allegedly Showing Ukrainian Drones Over Moscow Was Generated Using Artificial Intelligence

On June 1, 2026, a 37-second video was posted on YouTube by @CuongLuong-r2n. The video purported to show Ukrainian drones flying over Moscow, the capital of Russia. The accompanying description claimed that Ukraine had launched an attack on Moscow using more than 400 unmanned aerial vehicles (UAVs). The same video was subsequently uploaded on YouTube on June 2, 2026, by another user, @strker2000.

 

 

However, subsequent investigations revealed that both videos were generated using artificial intelligence. The footage was analyzed using HIVE Moderation, which determined that the content had been created with AI-based tools.

Further examination using Google SynthID indicated that the videos did not depict authentic footage but were instead generated through artificial intelligence or related digital technologies. The analysis highlighted several indicators of synthetic production, including unnatural drone flight patterns and multiple visual inconsistencies, which strongly suggested AI generation.

 

At the conclusion of both YouTube videos, it was noted that the content had previously been shared on Instagram, indicating that YouTube was not the original source. A reverse image search was therefore conducted, revealing that the video was first uploaded to Instagram on June 1, 2026, by “NEWS_02025.” The Instagram version received 505 likes and 55 comments within less than 24 hours.

 

In conclusion, the video initially shared on Instagram and subsequently reposted on YouTube was generated using artificial intelligence and does not depict real events. This case demonstrates how AI-generated content can reach large audiences through cross-platform reposting and gradually be perceived as authentic footage. Particularly in the context of international conflicts and security-related issues, it is essential to verify visual content using technical detection tools and cross-check it against reliable sources.

 

 

If you suspect that a video, image, or audio file has been created using artificial intelligence or deepfake technology and would like free assistance in verifying its authenticity, you may send the link to the content or the file itself to allaboutdeepfake@gmail.com.

SHIFTING NARRATIVES: A COMPARATIVE ANALYSIS OF ISLAMIC STATE OF IRAQ AND SYRIA (ISIS) SUPPORTERS' TWITTER HASHTAG USAGE IN TÜRKIYE BEFORE AND AFTER ITS TERRITORIAL DEFEAT

This study examines the evolution of hashtags used by Turkish supporters of the Islamic State of Iraq and Syria (ISIS) on Twitter, comparing the predefeat period (2014–2018) with the postdefeat period (2019–2022). The analysis encompasses 312,197 tweets to identify thematic shifts and network structures. In the predefeat phase, hashtags were primarily centered on geopolitical conflicts and political discourse, with prominent hashtags like #islamdevleti (Islamic State) and #incirlikkapatilsin (Incirlik Base must be closed). The network analysis revealed a main cluster of interconnected hashtags alongside smaller, niche groups. Postdefeat, the focus shifted towards humanitarian aid, financial support, and religious themes, with hashtags such as #sadaka (charity) and #infak (alms) becoming more prominent. This period exhibited multiple smaller, independent hashtag clusters, reflecting a more fragmented thematic focus. Despite these changes, core hashtags like #islamdevleti (Islamic State) and #hilafettakip (follow the caliphate) remained consistent, indicating enduring support for ISIS ideologies. The study underscores the adaptability of terrorist propaganda strategies in response to evolving circumstances and highlights the dynamic nature of online extremist activities. The findings contribute to a deeper understanding of how online platforms are leveraged by terrorist supporters to sustain and evolve their narratives over time.

Keywords: Twitter hashtags, terrorist propaganda, social media extremism, ISIS Turkish supporters, hashtag network analysis 

LINK: https://dergipark.org.tr/en/pub/ijshs/article/1853490

Deepfake Survey

I have prepared a survey as part of my postdoctoral research project at the Taiwan Foundation for Democracy. I would be very grateful for your participation. All participant information will remain strictly confidential and will not be disclosed under any circumstances. The results will not be used in any academic publication without prior ethical approval and will be used solely for the Taiwan Foundation for Democracy’s final report.

LINK: https://docs.google.com/forms/d/e/1FAIpQLSfrpkGSoYSb9lc68nKh5iHEJ8bkHabyKPQXvKvwegMhAtZRZQ/viewform?usp=dialog

A Hashtag Perspective: Examining ISIS Supporter Activities on Twitter in Türkiye between 2019 and 2022

This study explores the Twitter activities of Turkish supporters of the Islamic State of Iraq and Syria (ISIS) from 2019 to 2022, focusing on hashtag usage patterns. As a central part of ISIS's online strategy, hashtags are pivotal in disseminating propaganda, coordinating campaigns, and soliciting support. By analyzing 202,327 tweets, this research offers insights into thematic priorities and interconnections within ISIS-related discourse. Employing descriptive and network analyses, key findings reveal a steady increase in ISIS-supportive tweets, the emergence of clusters around aid and familial support, and distinct, unconnected hashtag groups reflecting various narratives. Hashtags related to financial aid, such as #saveprisoners and #elholcamp, emerge as central, highlighting a covert system of funding through social media and encrypted communication. This paper underscores the complexity of ISIS's digital influence in Türkiye, emphasizing the need for multifaceted countermeasures involving tech platforms, security forces, and media awareness campaigns to combat online extremist activities effectively.

LINK: https://gnet-research.org/2024/08/07/a-hashtag-perspective-examining-isis-supporter-activities-on-twitter-in-turkiye-between-2019-and-2022/

A Hashtag Perspective: Examining ISIS Supporter Activities on Twitter in Türkiye between 2019 and 2022

Recent advancements in social media technologies have significantly impacted both individuals and terrorist organizations. This study examines the Twitter activities of ISIS's Turkish supporters from 2019 to 2022, focusing on the hashtags they used. The study employs a hashtag network analysis to explore the relationships and central themes among the hashtags used in 202,327 tweets by 666 different users. The analysis reveals a central cluster of hashtags related to various forms of aid, particularly financial support, often connected with hashtags like #elholcamp and #yoursisterinprisoncamp, which pertain to families of ISIS members detained in YPG-controlled camps. Additionally, Turkish supporters of ISIS solicit financial aid via Twitter, phone numbers, and Telegram, using religious hadiths to legitimize their efforts. The findings underscore the sophisticated use of social media by ISIS supporters to sustain their activities in Türkiye and beyond, highlighting the need for a multifaceted response involving tech companies, security forces, local communities, and the media. This collaboration is crucial to detect, report, and mitigate the misuse of social media for terrorist purposes and to educate the public about these activities.

LINK: https://gnet-research.org/2024/08/07/a-hashtag-perspective-examining-isis-supporter-activities-on-twitter-in-turkiye-between-2019-and-2022/

Comparison of Turkish and English-Speaking ISIS Sympathizers’ Twitter Content between 2015 and 2016

 

Abstract

The development of social media technologies has had a significant impact on individuals, organizations and societies. However, social media has not only affected people and communities, but also terrorist organizations have started to use social media platforms effectively. The Islamic State of Iraq and Syria (ISIS) is one such group that actively utilizes social media. Social media has played a critical role in formulating and disseminating ISIS’s strategies. Twitter is one of the most effective social media platforms used by ISIS, and it actively uses Twitter in predominantly Muslim countries such as Turkey. In this article, I use a dictionary-based method to compare and analyze 29,419 tweets from English-speaking supporters of ISIS and 40,526 tweets from Turkish supporters of ISIS between 2015 and 2016.

Keywords: Twitter analysis; Islamic State of Iraq and Syria (ISIS); Turkish and English-speaking ISIS supporters on Twitter; dictionary-based analysis

Link: https://brill.com/view/journals/iss/aop/article-10.1163-27730611-bja10013/article-10.1163-27730611-bja10013.xml

Examining ISIS's Turkish Sympathizers on Twitter

Abstract

Social media platforms have become a part of people's daily lives. However, developing social media technologies have affected not only people but also terrorist organizations such as the Islamic State of Iraq and Syria (ISIS), and social media has become an essential part of ISIS's strategies. ISIS effectively uses many social media platforms, especially Twitter, for propaganda, recruitment, and creating fear among people. ISIS also actively uses Twitter in Turkey. However, the number of academic studies focusing on the behavior, structure, communication, and relationship networks of ISIS sympathizers in Turkey is limited. Therefore, the main purpose of this study is to reveal the structure, behavior, communication, and relationship networks of ISIS's Turkish sympathizers. Accordingly, this study focuses on the structure, behavior, communication, and relationship networks of ISIS's Turkish sympathizers. I will analyze them within four main analytical steps. The basic characteristics, structures, behaviors, and relationship networks of 2079 Turkish ISIS sympathizers are examined with the R computer program, and many remarkable findings are reached as a result of the analysis.

Keywords: ISIS' Turkish Supporters, Twitter Analysis, Network Analysis, Correlation Analysis, Social Media

LINK: https://dergipark.org.tr/tr/pub/icps/issue/74445/1183919

SentiStrength

 

SentiStrength is a software program that analyzes sentiment. SentiStrength gives sentiment results in three types. First, it gives us the results in binary form. In other words, it gives the sentiment results as positive or negative. Second, it gives it as a trinary. That is, the results are presented as positive, negative or neutral. Finally, it gives sentiment results as a single scale. In other words, sentiment results are given on a scale between -5 and +5. SentiStrength supports many languages such as German, English, Finnish and Turkish and is capable of sentiment analysis of texts written in these languages. The SentiStrength program is completely free.

10108 tweets about online food ordering services are analyzed with the SentiStrength program to explain this software in depth. The main problem we encounter at this stage is that the SentiStrength program only accepts documents with the ".txt" extension. If the text you want to analyze is ".xlsx" extended, you should deal with this issue first. Unfortunately, the file I would to analyse has the ".xlsx" extension. For this reason, I will first convert the section I want to examine in the excel file to .txt format. In this context, delete the sections except the section we want to analyze, and only the column we want to analyze remains in our file. In the next step, we need to remove the duplicates to avoid recounting the same tweets. In Excel, we can remove duplicates using the “Data-> Remove Duplicates” function. The logo you see marked is the logo that belongs to the "remove duplicates" function.

Then save our excel file, which we cleaned from repetitions, as unicode text (.txt). In the next step, open the SentiStrength program and select the "Analyze ALL Texts in File (each line separately)" function in the "Sentiment Strength Analysis" section.

Next, let's select the .txt file we want to analyze. Before the analysis starts, SentiStrength will ask if you want to add a header line to the resulting file, and we need to select "Yes". SentiStrength will ask us which column to use for analysis and we can directly write "1" here.

If this image occurs, it means that our analysis is complete. However, at this stage, the problem we encountered at the beginning reoccurs. The results are saved on our computer with the .txt extension.

It will be useful to copy and paste the results with .txt extension to the excel file so that we can see the results more clearly.

At the last stage, we will have an excel file with 5 columns such as positive, negative and EmotionRationale. When we look at the results, it is seen that there are many -1 and +1. -1 means not negative or neutral. +1 means not positive or neutral. Between 2 and 4 is positive and 5 is extremly positive. On the other hand, between -2 and -4 is negative and -5 is extremely negative.

Finally, we can add another column named "score" next to the negative and positive columns in the excel file and see the general sentiment result. For this process, we need to use the following formula; "=C2+D2". The results we get with this formula will give the overall result of each tweet we analyzed.

 ISIS Religious and Extremist Propaganda on Social Media: Dictionary-Based Study of Twitter

Abstract

The world had faced with many terrorist organizations until 2014. However, after 2014, the world faced with the most complicated terrorist organization. This terrorist organization is ISIS or Islamic State of Iraq and Syria. ISIS has been running a more different propaganda campaign, emphasizing the state-building and welfare schemes run by this organization and these elements make ISIS more complicated. ISIS has been very well integrated into the new technology such as social media and smartphone and ISIS has been using them very effectively. Especially Twitter has become a major component of ISIS social media movement. Twitter was used to spread sensationalistic ISIS photos and videos across the Twitter users. While ISIS spread fear and messages on twitter, at the same time it also gained supporters. However, it is seen that ISIS’ sympathizer uses different jargons in terms of their number of followers in twitter. As a result of my research, I found that users with more followers used a stronger violence jargon on Twitter, while users with fewer followers using a softer and more religious language. Users with less followers were an emphasis on unity and religion, while users with more followers encouraging physical violence such as lone wolf attacks and killing enemy appeared more often on Twitter. Dictionary-based analysis of ISIS' and its sympathizers' tweets were performed. This dictionary-based research creates a typology to explain and categorize tweets from ISIS and its followers. For reliability, "Split-half test" was applied to the results and similar results were reached.

Keywords: ISIS, Twitter, Dictionary-Based Analysis, Propaganda

RELATED LINK: https://smallwarsjournal.com/jrnl/art/isis-religious-and-extremist-propaganda-social-media-dictionary-based-study-twitter

2020 General Election in Taiwan

The results of the Taiwan general elections had been eagerly awaited for a long time. Especially the results of the local elections in 2018 made these general elections more remarkable. In addition, the protests in Hong Kong increased the importance of the Taiwan general elections.

In this article, I will first describe my observations in general elections. Then I will briefly explain the results of Twitter analysis about Taiwan general election, which I analyzed with the text analysis method.

OBSERVATION

In the morning, I started following the general elections in Taiwan. At the same time, I also tried to feel the political atmosphere inside country. Because of that reason, I talked with some of my Taiwanese friends. Around 7 PM, the election results began to be announced. Around 7.30pm, I first went to the KMT's headquarter in Kaohsiung. However, the KMT headquarter was quite empty. The most important reason for this was that DPP was ahead by far, according to the first results. Another important reason was that pan-blue party sympathizers did not trust their candidates.

Around 8 pm, the results began to be clear and I decided to go to the DPP's rally. The rally area was quite crowded. It was as crowded as the KMT's rally, which won last year's local elections. The excitement and joy of people in the rally area was quite interesting.

As a result of the local elections in 2018, the Green Party(DPP) lost the local elections. As a result of the defeat, the DPP leader and Taiwanese president Tsai Ing-Wen resigned from party leadership. But Tsai Ing-Wen, who withdrew her resignation, won this year's general elections.

With the results, the KMT candidate Han Kuo-yu made his speech first. About an hour later, Tsai Ing wen, the winner of the election, made her speech. However, the first thing that caught my attention during this speech was that Tsai Ing Wen spoke quite calmly and seriously. Unlike Ing Wen, DPP sympathizers were extremely happy.

In her speech, Ing wen praised Taiwan's democracy and stated that relations with China will continue in the same way.

TWITTER ANALYSIS

2000 English tweets about Taiwanese general elections between the January 1st and January 20th were examined with R computer program. First, the most commonly used words were found in these 2000 tweets. The words Economy, Growth, Hong Kong Protests, independence and victory are the most used words in 2000 tweets.

Most of the tweets are positive about Ing-Wen and DPP's victory.

Words like freedom, peaceful, democracy, growth and hope are the most commonly used positive words. Words such as infrared, protest, fight and Xi Jinping are the most commonly used negative words. 

Secondly, sentiment analysis of these 2000 tweets was analyzed. The highest sentiment in these tweets is trust. Then comes anticipation and fear.

Words like president, democracy, freedom, integrity, alliance and brilliant are the words with the highest trust sentiment. Words like young, vote, result and prevention are the words with the highest sense of anticipation. Words like Fight, Interfere, and Xi Jinping are the words with the highest sense of fear.

CONCLUSION

In conclusion, DPP sympathizers were very happy and hopeful at the DPP rally. Twitter analysis results gave similar results.

However, despite all this happiness and anticipation, it is a matter of curiosity how China-Taiwan relations and Ing-Wen's attitude towards China will change and shape.

Trend Topic Analysis with R

Twitter is one of the most popular social media applications in recent years. With the R program, it is possible to analyze many data from Twitter. Two of these analyzes are sentiment and polarity analysis.

These analyzes were applied to one of the trend topics on Twitter. For this purpose, the first trend topics in the world were found with "getTrend ()" function. As a results of this research, the most popular trend topic is #gretathunberg.

Afterwards, tweets were cleaned and sentiment and polarity analysis were performed.

First, polarity analysis was performed. As a results of this analysis, the majority of tweets related to #gretathumberg are positive.

Figure 1: polarity analysis

Secondly, sentiment analysis was performed. According to this analysis, anticipation and trust are the most dominant feelings among tweets.

Figure 2: Sentiment analysis (second column is anticipation.)

Finally, the most popular devices, which are used to post on twitter, were analyzed. Twitter web app and twitter android are the most used software.

Figure 3: Most used software and devices

Terrorism Dilemma

Terrorism has been one of the most remarkable issues in recent years. Many scholars argue about terrorism. However, the lack of a definition of terrorism complicates the issue.

The most acceptable definition of terror in the world is the CIA's definition of terror. This study uses the CIA's definition of terrorism. According to Central Intelligence Agency (2007), terrorism means premeditated, politically motivated violence perpetrated against noncombatant targets by subnational groups or clandestine agents, usually intended to influence an audience.

This definition is quite clear. Based on this definition, the YPG in Syria is a terrorist organization. However, many Western countries and the United States do not recognize YPG as terrorists. But this organization has caused the deaths of many innocent people in Turkey. Nevertheless, the media of many countries continue to have positive news about this organization. In addition, there are also positive news about the terrorist organization on Twitter.

For this purpose, sentiment and polarity analysis related with YPG in CNN, The New York Times and Twitter was performed.

                       

      

                                      Figure 1: Polarity result of CNN

Firstly, CNN's latest news about ypg is examined. The analysis revealed that the CNN's news was very positive about YPG. The most commonly used sentiment in the news about YPG is trust.

                               

                                          Figure 2: Sentiment result of CNN

            Secondly, the last news of the new york times about ypg was analyzed. Similar results were obtained with CNN. The new york times ypg news is also very positive. The most commonly used sentiment in the New York Times’ news about YPG is trust.

                                                Figure 3: Polarity result of New York Times

                                               Figure 4: Sentiment result of New York Times

Finally, the last 100 tweets about YPG on Twitter were analyzed. Twitter also has positive tweets about YPG, like CNN and New York Time. The most commonly used sentiment in twitter about YPG is fear. Tweets about ISIS raise the fear rate. That’s why fear was the most common sentiment in this anaysis.

                                      Figure 5: Polarity result of Tweets

                                      Figure 6: Sentiment result of Tweets

As seen above, there are positive views on YPG, which many countries recognize as terrorist organizations, in the media and social media. 

The relationship between Twitter and ISIS

In recent years, great development has been seen in technology. One of the most important of these technologies is social media.

The development of social media has played an important role in many social protests in recent years in the world. The best example of such social protests is the Arab Spring period.

During the Arab Spring, social media played an important role in helping people get news and organize. However, this development of social media is not only used by innocent people. Especially in recent years, terrorist organizations also benefit from the development of social media.

The most active terrorist organization on social media is ISIS. In particular, ISIS was using Twitter very actively. %90 of ISIS social media was conducted via twitter. ISIS sympathizers posted 200000 tweets per day.

Therefore, in this study, tweets of ISIS sympathizers between 2015-2016 were examined. The results of the research are as follows;

Most active 10 twitter users about ISIS
username,                         sum(weight)
Uncle_SamCoco,             1610
mobi_ayubi,                     1071
WarReporter1,                 706
warrnews,                         657
melvynlion,                      640
RamiAlLolah,                  606
MaghrabiArabi,               450
_IshfaqAhmad,                430
AsimAbuMerjem,           289
NaseemAhmed50,           251

The research was first started to analyze one of the most active users. This user is war breaking news. This user's most commonly used words are as follows;

[1] "after"       "against"     "aleppo"      "alqassam"    "amp"         "and"         "are"         "army"        "assad"       "attack"      "border"   
[12] "breaking"    "captured"    "city"        "civilians"   "claims"      "clashes"     "damascus"    "destroyed"   "dozens"      "during"      "fallujah" 
[23] "fight"       "fighters"    "for"         "forces"      "from"        "fsa"         "gaza"        "hamas"       "have"        "homs"        "huge"     
[34] "injured"     "iranian"     "iraq"        "iraqi"       "isis"        "israel"      "israeli"     "killed"      "least"       "militant"    "militants"
[45] "military"    "more"        "mosul"       "mujahid"     "near"        "new"         "news"        "nidalgazaui" "north"       "northern"    "not"     
[56] "now"         "offensive"   "one"         "over"        "palmyra"     "people"      "province"    "rebels"      "regime"      "reports"     "russia"   
[67] "russian"     "saa"         "saudi"       "sham"        "shiite"      "shot"        "soldiers"    "south"       "southern"    "suicide"     "syria"   
[78] "syrian"      "that"        "the"         "their"       "they"        "this"        "today"       "troops"      "turkey"      "turkish"     "video"   
[89] "war"         "warnews"     "was"         "were"        "who"         "will"        "with"        "ypg"

In addition to the war breaking news, the tweets of the two users were analyzed also. The first user was Fahad al-Kuwaiti.

Fahad mostly used words such as state, mujahideen and Islamic. After Fahad, the tweets of Flames of Haqq were examined.

These are the most popular words used by Flames of Haqq. In addition, the detailed list of words used by Haqq is as follows.

[1] "ahmad"        "alasma"       "allah"        "amp"          "and"          "are"          "cerantonio"   "follow"       "for"          "from"     
[11] "isis"         "jibril"       "johnsonsbot"  "just"         "keep"         "killed"       "musa"         "mustaklash"   "nby"          "one"       
[21] "our"          "palmyra"      "please"       "rer"          "sparksofirha" "str"          "that"         "the"          "this"         "today"     
[31] "ulhusna"      "video"        "warreporter"  "who"          "with"         "wwayf"        "you"          "your"

As seen in all three examples, the most commonly used words are words such as kill or killed, video, state and war. ISIS sympathizers positively propagate ISIS with these words. As a result, ISIS sympathizers make positive propaganda through twitter. The authorities should take action on this matter.