The Islamic State’s information warfare

2017 ◽  
Vol 17 (2) ◽  
pp. 258-280 ◽  
Author(s):  
Alexandra A. Siegel ◽  
Joshua A. Tucker
Keyword(s):  
Social Media ◽  
Linguistically Diverse ◽  
Information Warfare ◽  
Core Network ◽  
Policy Goals ◽  
Social Media Platforms ◽  
Search Data ◽  
Online Strategy ◽  
Twitter Users

Abstract How successful is the Islamic State’s online strategy? To what extent does the organization achieve its goals of attracting a global audience, broadcasting its military successes, and marketing the Caliphate? Using Twitter and YouTube search data, collected throughout 2015 and early 2016, we assess how suspected ISIS accounts, sympathizers, and opponents behave across two social media platforms, offering key insights into the successes and limitations of ISIS’s information warfare strategy. Analyzing the tweet content and metadata from 16,364 suspected ISIS accounts, we find that a core network of ISIS Twitter users are producing linguistically diverse narratives, touting battlefield victories and depicting utopian life in the Caliphate. Furthermore, a dataset of over 70 million tweets, as well as analysis YouTube search data, indicates that although pro-ISIS content spreads globally and remains on message, it is far less prolific than anti-ISIS content. However, this anti-ISIS content is not necessarily anti-extremist or aligned with Western policy goals.

Comparing Representation of Depression on Reddit and Twitter Social Media Platforms (Preprint)

2020 ◽  
Author(s):  
Ethan Kaji ◽  
Maggie Bushman
Keyword(s):  
Mental Health ◽  
Social Media ◽  
Content Analysis ◽  
Relative Frequency ◽  
Social Activity ◽  
Social Media Platforms ◽  
Dsm Iv ◽  
Twitter Users

BACKGROUND Adolescents with depression often turn to social media to express their feelings, for support, and for educational purposes. Little is known about how Reddit, a forum-based platform, compares to Twitter, a newsfeed platform, when it comes to content surrounding depression. OBJECTIVE The purpose of this study is to identify differences between Reddit and Twitter concerning how depression is discussed and represented online. METHODS A content analysis of Reddit posts and Twitter posts, using r/depression and #depression, identified signs of depression using the DSM-IV criteria. Other youth-related topics, including School, Family, and Social Activity, and the presence of medical or promotional content were also coded for. Relative frequency of each code was then compared between platforms as well as the average DSM-IV score for each platform. RESULTS A total of 102 posts were included in this study, with 53 Reddit posts and 49 Twitter posts. Findings suggest that Reddit has more content with signs of depression with 92% than Twitter with 24%. 28.3% of Reddit posts included medical content compared to Twitter with 18.4%. 53.1% of Twitter posts had promotional content while Reddit posts didn’t contain promotional content. CONCLUSIONS Users with depression seem more willing to discuss their mental health on the subreddit r/depression than on Twitter. Twitter users also use #depression with a wider variety of topics, not all of which actually involve a case of depression.

scholarly journals The public accountability of social platforms: lessons from a study on bots and trolls in the Brexit campaign

2018 ◽  
Vol 376 (2128) ◽  
pp. 20180003 ◽  
Author(s):  
Marco Bastos ◽  
Dan Mercea
Keyword(s):  
Social Media ◽  
Large Scale ◽  
Ethical Issues ◽  
Lessons Learned ◽  
Information Warfare ◽  
The Public ◽  
Social Media Platforms ◽  
Application Programming ◽  
Access To Data ◽  
The Uk

In this article, we review our study of 13 493 bot-like Twitter accounts that tweeted during the UK European Union membership referendum debate and disappeared from the platform after the ballot. We discuss the methodological challenges and lessons learned from a study that emerged in a period of increasing weaponization of social media and mounting concerns about information warfare. We address the challenges and shortcomings involved in bot detection, the extent to which disinformation campaigns on social media are effective, valid metrics for user exposure, activation and engagement in the context of disinformation campaigns, unsupervised and supervised posting protocols, along with infrastructure and ethical issues associated with social sciences research based on large-scale social media data. We argue for improving researchers' access to data associated with contentious issues and suggest that social media platforms should offer public application programming interfaces to allow researchers access to content generated on their networks. We conclude with reflections on the relevance of this research agenda to public policy. This article is part of a discussion meeting issue ‘The growing ubiquity of algorithms in society: implications, impacts and innovations'.

Multidimensional Mappings of Political Accounts for Malicious Political Socialbot Identification

2019 ◽  
pp. 263-348
Author(s):  
Shalin Hai-Jew
Keyword(s):  
Social Media ◽  
Information Warfare ◽  
Russian Government ◽  
Web Based ◽  
Content Sharing ◽  
Social Media Platforms ◽  
Media Platform ◽  
Strategic Messaging ◽  
Geographical Locations ◽  
The U.S

Malicious political socialbots used to sway public opinion regarding the U.S. government and its functions have been identified as part of a larger information warfare effort by the Russian government. This work asks what is knowable from a web-based sleuthing approach regarding the following four factors: 1) the ability to identify malicious political socialbot accounts based on their ego neighborhoods at 1, 1.5, and 2 degrees; 2) the ability to identify malicious political socialbot accounts based on the claimed and linked geographical locations of their accounts, their ego neighborhoods, and their #hashtag networks; 3) the ability to identify malicious political socialbot accounts based on their strategic messaging (content, sentiment, and language structures) on respective social media platforms; and 4) the ability to identify and describe “maliciousness” in malicious political socialbot accounts based on observable behaviors on that account on three social media platform types: (a) microblogging, (b) social networking, and (c) crowd-sourced encyclopedia content sharing.

scholarly journals Electronic Cigarette Users' Perspective on the COVID-19 Pandemic: Observational Study Using Twitter Data (Preprint)

2020 ◽  
Author(s):  
Yankun Gao ◽  
Zidian Xie ◽  
Dongmei Li
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Topic Modeling ◽  
Viral Infections ◽  
Application Programming Interface ◽  
Electronic Cigarette ◽  
Twitter Data ◽  
Social Media Platforms ◽  
Twitter Users ◽  
Public Health Practitioners

BACKGROUND Previous studies have shown that electronic cigarette (e-cigarette) users might be more vulnerable to COVID-19 infection and could develop more severe symptoms if they contract the disease owing to their impaired immune responses to viral infections. Social media platforms such as Twitter have been widely used by individuals worldwide to express their responses to the current COVID-19 pandemic. OBJECTIVE In this study, we aimed to examine the longitudinal changes in the attitudes of Twitter users who used e-cigarettes toward the COVID-19 pandemic, as well as compare differences in attitudes between e-cigarette users and nonusers based on Twitter data. METHODS The study dataset containing COVID-19–related Twitter posts (tweets) posted between March 5 and April 3, 2020, was collected using a Twitter streaming application programming interface with COVID-19–related keywords. Twitter users were classified into two groups: Ecig group, including users who did not have commercial accounts but posted e-cigarette–related tweets between May 2019 and August 2019, and non-Ecig group, including users who did not post any e-cigarette–related tweets. Sentiment analysis was performed to compare sentiment scores towards the COVID-19 pandemic between both groups and determine whether the sentiment expressed was positive, negative, or neutral. Topic modeling was performed to compare the main topics discussed between the groups. RESULTS The US COVID-19 dataset consisted of 4,500,248 COVID-19–related tweets collected from 187,399 unique Twitter users in the Ecig group and 11,479,773 COVID-19–related tweets collected from 2,511,659 unique Twitter users in the non-Ecig group. Sentiment analysis showed that Ecig group users had more negative sentiment scores than non-Ecig group users. Results from topic modeling indicated that Ecig group users had more concerns about deaths due to COVID-19, whereas non-Ecig group users cared more about the government’s responses to the COVID-19 pandemic. CONCLUSIONS Our findings show that Twitter users who tweeted about e-cigarettes had more concerns about the COVID-19 pandemic. These findings can inform public health practitioners to use social media platforms such as Twitter for timely monitoring of public responses to the COVID-19 pandemic and educating and encouraging current e-cigarette users to quit vaping to minimize the risks associated with COVID-19.

scholarly journals A simulated cyberattack on Twitter: Assessing partisan vulnerability to spear phishing and disinformation ahead of the 2018 U.S. midterm elections

First Monday ◽  
2018 ◽  
Author(s):  
Michael Bossetta
Keyword(s):  
Social Media ◽  
Private Information ◽  
Right Wing ◽  
Left Wing ◽  
Fake News ◽  
Breaking News ◽  
Media Companies ◽  
Midterm Elections ◽  
Social Media Platforms ◽  
Twitter Users

State-sponsored “bad actors” increasingly weaponize social media platforms to launch cyberattacks and disinformation campaigns during elections. Social media companies, due to their rapid growth and scale, struggle to prevent the weaponization of their platforms. This study conducts an automated spear phishing and disinformation campaign on Twitter ahead of the 2018 United States midterm elections. A fake news bot account — the @DCNewsReport — was created and programmed to automatically send customized tweets with a “breaking news” link to 138 Twitter users, before being restricted by Twitter.Overall, one in five users clicked the link, which could have potentially led to the downloading of ransomware or the theft of private information. However, the link in this experiment was non-malicious and redirected users to a Google Forms survey. In predicting users’ likelihood to click the link on Twitter, no statistically significant differences were observed between right-wing and left-wing partisans, or between Web users and mobile users. The findings signal that politically expressive Americans on Twitter, regardless of their party preferences or the devices they use to access the platform, are at risk of being spear phished on social media.

scholarly journals Connecting the Urological Community : The #UroSoMe Experience

2019 ◽  
Vol 2 (2) ◽  
pp. e20-e29 ◽  
Author(s):  
Kalyan Gudaru ◽  
Leonardo Tortolero Blanco ◽  
Daniele Castellani ◽  
Hegel Trujillo Santamaria ◽  
Marcela Pelayo-Nieto ◽  
...  
Keyword(s):  
Social Media ◽  
Working Group ◽  
Efficient Manner ◽  
The Social ◽  
Social Media Platforms ◽  
Twitter Account ◽  
Group Members ◽  
Twitter Users ◽  
Use Of Social Media ◽  
Twitter Activity

Background and Objectives There is an increasing use of social media amongst the urological community. However, it is difficult to identify urological data on various social media platforms in an efficient manner. We proposed a hashtag, #UroSoMe, to be used when posting urology-related content in the social media platforms. The objectives of this article are to describe how #UroSoMe was developed, and to report the data of the first month of #UroSoMe.   Material and Methods The hashtag, #UroSoMe, was introduced to the urological community. The #UroSoMe working group was formed, and the members actively invited and encouraged people to use the hashtag #UroSoMe when posting urology-related contents. After the #UroSoMe (@so_uro) platform on twitter had grown to more than 300 users, the first live event of online case discussion, i.e. #LiveCaseDiscussions, was conducted. A prospective observational study of the hashtag #UroSoMe Twitter activity during the first month of its usage from 14 December 2018 to 13 January 2019 was evaluated. Outcome measures included number of users, number of tweets, user location, top tweeters, top hashtags used and interactions. Analysis was performed using NodeXL (Social Media Research Foundation; California, USA; https://www.smrfoundation.org/nodexl/), Symplur (https:// www.symplur.com) and Twitonomy (https://www.twitonomy.com).   Results The first month of #UroSoMe activity documented 1373 tweets/retweets by 1008 tweeters with 17698 mentions and 1003 replies. The #LiveCaseDiscussions was able to achieve a potential reach of 2,033,352 Twitter users. The top tweets mainly included cases presented by #UroSoMe working group members during #LiveCaseDiscussions. The twitonomy map showed participation from 214 geographical locations. The major groups of participants using the hashtag #UroSoMe were ‘Researcher/Academic’ and ‘Doctor’. The twitter account of #UroSoMe (@so_uro) has now grown to more than 1000 followers.   Conclusions Social media is an excellent platform for interaction amongst the urological community. The results demonstrated that #UroSoMe was able to achieve wide spread engagement from all over the world.

scholarly journals To Whom Do Politicians Talk and Listen? : Mapping Swiss Politicians’ Public Sphere on Twitter

2020 ◽  
Vol 2 (2) ◽  
pp. 175-202
Author(s):  
Tobias R. Keller
Keyword(s):  
Social Media ◽  
Public Sphere ◽  
The Public ◽  
Automated Content Analysis ◽  
Social Media Platforms ◽  
The Media ◽  
Twitter Users ◽  
The Public Sphere ◽  
Mps I ◽  
Ordinary Citizens

Abstract Politicians use social media platforms such as Twitter to connect with the public. However, it remains largely unknown who constitutes the public sphere to whom politicians actually connect, talk, and listen. Focusing on the Twitter network of all Swiss MPs, I identified 129,063 Twitter users with whom politicians connected (i.e., their follower‐followee network) or with whom they interacted (e.g., [were] replied to or retweeted). I qualitatively analyzed top connected, talking, and listening MPs, and conducted a semi-automated content analysis of the Twitter users to classify them (N = 70.589). Politicians’ audience consists primarily of ordinary citizens, who also react most often to the politicians’ messages. However, politicians listen more often to actors close to politics and the media than to ordinary citizens. Thus, politicians navigate between engaging with everyone without losing control over the communication situation and address key multipliers such journalist to get their messages out.

Discussion, news information, and research sharing on social media at the onset of Covid-19

2021 ◽  
Author(s):  
Hyejin Park ◽  
J. Patrick Biddix ◽  
Han Woo Park
Keyword(s):  
Social Media ◽  
Social Network ◽  
Early Stage ◽  
World Health ◽  
Network Structures ◽  
The Social ◽  
Social Media Platforms ◽  
Twitter Users ◽  
Statistical Relationships ◽  
Health Organization

Social media platforms provide valuable insights into public conversations. They likewise aid in understanding current issues and events. Twitter has become an important virtual venue where global users hold conversations, share information, and exchange news and research. This study investigates social network structures among Twitter users with regard to the Covid-19 outbreak at its onset and its spread. The data were derived from two Twitter datasets by using a search query, “coronavirus,” on February 28th, 2020, when the coronavirus outbreak was at a relatively early stage. The first dataset is a collection of tweets used in investigating social network structures and for visualization. The second dataset comprises tweets that have citations of scientific research publications regarding coronavirus. The collected data were analyzed to examine numerical indicators of the social network structures, subgroups, influencers, and features regarding research citations. This was also essential to measure the statistical relationships among social elements and research citations. The findings revealed that individuals tend to have conversations with specific people in clusters regarding daily issues on coronavirus without prominent or central voice tweeters. Tweets related to coronavirus were often associated with entertainment, politics, North Korea, and business. During their conversations, the users also responded to and mentioned the U.S. president, the World Health Organization (WHO), celebrities, and news channels. Meanwhile, people shared research articles about the outbreak, including its spread, symptoms related to the disease, and prevention strategies. These findings provide insight into the information sharing behaviors at the onset of the outbreak.

Characterization of depression in Spanish tweets: a behavioral and linguistic analysis (Preprint)

2019 ◽  
Author(s):  
Angela Leis ◽  
Francesco Ronzano ◽  
Miguel A. Mayer ◽  
Laura I. Furlong ◽  
Ferran Sanz
Keyword(s):  
Social Media ◽  
Mental Disorders ◽  
Healthcare Services ◽  
Linguistic Features ◽  
Second Person ◽  
Daily Lives ◽  
Control Dataset ◽  
Social Media Platforms ◽  
Twitter Users ◽  
Selection Of

BACKGROUND Mental disorders have become a major concern in public health and are one of the main causes of the overall disease burden worldwide. Social media platforms allow us to observe the activities, thoughts and feelings of people’s daily lives, including those of patients suffering from mental disorders. There are studies that have analyzed the influence of mental disorders, including depression, in the behavior of social media users, but they have been usually focused on messages written in English. OBJECTIVE The aim of this study is to identify the linguistic features of tweets in Spanish and the behavioral patterns of Twitter users that generate them, which could suggest signs of depression. METHODS This study was developed in two steps. In the first step, the selection of users and the compilation of tweets were performed. Three datasets of tweets were created, a depressive users dataset (made up of the timeline of 90 users who explicitly mention that they suffer from depression), a depressive tweets dataset (a manually curated selection of tweets from the previous users that include expressions indicative of depression) and a control dataset (made up of the timeline of 450 randomly selected users). In the second step, the comparison and analysis of the three datasets of tweets were carried out. RESULTS In comparison to the control dataset, the depressive users are less active in posting tweets, doing it more frequently between 23:00 and 6:00 (P<.001). The percentage of nouns used by the control dataset almost doubles that of the depressive users (P<.001). By contrast, the use of verbs is more common in the depressive users dataset (P<.001). The first-person singular pronoun was by far the most used in the depressive users dataset (80%) and the first and the second person plural were the less frequent (0.4% in both cases), being this distribution different to that of the control dataset (P<.001). Sadness and anger emotions were the most common in the depressive users and depressive tweets datasets with significant differences when comparing these datasets with the control one (P<.001). As for negation words, they were detected in the 34% and 46% of the tweets in the depressive users and depressive tweets respectively, which are significantly different to the control dataset (P<.001). Negative polarity was more frequent in the depressive users (54%) and depressive tweets (65%) datasets than in the control one (43.5%) (P<.001). CONCLUSIONS Twitter users who are potentially suffering from depression modify the general characteristics of their language and the way they interact on social media. Based on these changes these users can be monitored and supported, thus introducing new opportunities for the study of depression and for providing additional healthcare services to people with this disorder.

Hacktivism and distributed hashtag spoiling on Twitter: Tales of the #IranTalks

First Monday ◽  
2018 ◽  
Author(s):  
Mahdi M. Najafabadi ◽  
Robert J. Domanski
Keyword(s):  
Social Media ◽  
High Frequency ◽  
Accurate Analysis ◽  
Organizational Network ◽  
Analysis Techniques ◽  
Social Trends ◽  
Comprehensive Plan ◽  
Social Media Platforms ◽  
Twitter Users ◽  
Final Agreement

The landmark Joint Comprehensive Plan of Action (JCPOA) was the final agreement of a series of tense nuclear negotiations between Iran and EU3+3 countries that started from September 2013, after which the Iranian people had elected a new president, and finalized in 2015. During several rounds of these negotiations, we noticed that some Twitter users were seemingly trying to distract people from the flow of latest news about the most trending negotiation’s hashtag, “#IranTalks”, by posting irrelevant tweets at a high frequency, that could be categorized as ‘spam’. We collected a sampling of all the tweets that contained the #IranTalks hashtag, and marked the distracting tweets based on some criteria. We populated a list of the spammers’ accounts and extracted their one-on-one friendship relationship (following/followed by). We applied social and organizational network analysis techniques and found strong evidence for the existence of an organization through which the accounts responsible for such tweeting behavior are connected. We believe the results of this study can stimulate more research about this social and organizational phenomenon and its possible impacts, and can help in better understanding and more accurate analysis of social trends on social media platforms.

Sign in / Sign up

Export Citation Format

Share Document