Telegram Online
Padre Harmon
Previous versions of Telegram used to linger on changing one's status from online to last seen just now for about 5-10 minutes. (Not documented, just my observation.) But I think they've fixed this in the latest version. Please update Telegram on all your devices and check if this problem still exists.
We provide a new text corpus from the social medium Telegram, which is rich in indirect forms of divisive speech. We scraped all messages from one channel of Donald Trump supporters, covering a large part of his presidency, from late 2016 until January 2021, including the January 6 Capitol riot. The discussion among the group members, over this long time period, includes the spread of disinformation, disparaging of out-group members, and other forms of harmful speech. To enable research into the role of harmful speech in political discourse, we added two types of annotations to the corpus: (i) automatic annotations of offensive language for all messages, and (ii) our own manual annotations of harmful language for a portion of the posts leading up to the January 2021 Capitol riot and its aftermath.
The content and metadata were mined using the Telethon1 Python package. This is an interface to the Telegram API which facilitates interaction with Telegram and application development. Our data also contains the metadata, including date and time of post creation, message ID, user ID, the ID of the message replied to, any attached media (e.g., image, video, sticker), as well as the message text itself. This may be useful for further research modelling the interactions among participants in the community.
As a result of the controversial nature of the data, 3,619 additional messages originally posted in the channel appear to have been deleted prior to collection, leaving blank message content, which we filtered out. This also reduced the initial 1,068 unique users to 521. Figure 1 illustrates this trend in 2018, as reflected in the small number of messages posted and the absence of new users.
The channel was chosen specifically to document online use of harmful language, among a like-minded group of users. This will allow follow-up studies to refine definitions and taxonomies of harmful speech and online harm in linguistics, philosophy, communication, and media studies.
In addition, the data can be used to validate computational methods for harmful language detection. Various computational methods have already been developed based on data from other media and domains, e.g., discourse around immigration on Facebook, gender on Twitter (see Poletto et al. 2020 for a comprehensive overview of available datasets). Our data suggests there is utility in evaluating these methods based on novel data, such as our corpus. This is because the in-group community that tends to populate Telegram channels has a different dynamic than that of more open and heterogenous communities present on Facebook, Twitter, or YouTube. The enclosed nature of the Telegram community is arguably a key factor to an environment amenable to incubating hatred, and where harmful language is the norm.
Reliable algorithms for detecting online harmful speech are so much needed in the context of our societies, in which hate speech, misinformation and right-wing extremism are on the rise. There is, thus, an immediate practical application of our data and analysis to research on digital language.
In addition to contributing to computational methods for detecting harmful speech, our corpus is also useful to validate general methods in natural language processing, such as coreference resolution and dialogue act tagging, which have been developed based on data from other media. The corpus can also be used as a resource for teaching in corpus and computational linguistics.
Notably, given the time period we chose, leading up to and following the January 2021 US Capitol riot, the corpus provides valuable data for political scientists, sociologists, and communication scientists, interested in the conditions and consequences of critical political events in the United States, how they shape public opinion by mobilizing and radicalizing layers of population into a dangerous right-wing base.
Finally, it is worth flagging that as a corpus assembled by mining a social media channel, the data has certain limitations. While this particular corpus may be of interest in the current political climate of US politics, it may lose its topical impact or become superseded by future political changes and trends in public discourse. Thus, though most of the available posts were created within the last few months, they may become obsolete for future studies relying on more recent data.
Another inherent difficulty with online content in general is that supplementary material, such as URL links included in the posts, may be deleted, and thus render the context for the content contributions insufficient or simply unavailable. This is unfortunately the fragile nature of online content and data, which is a common problem for this type of research.
Given these difficulties, our goal is to make a contribution both in terms of providing empirical data of an increasing corrosive force in our democracies in the form of online harm, and in terms of refining our computational tools to improve performance in detection of harmful speech.
Our data collection is created in accordance with the FAIR principles (Wilkinson et al. 2016) meaning that it is Findable, Accessible, Interoperable and Reusable, as it is publicly available through the OSF platform; it is open-source and presented in two widely used formats, TSV and JSON; in (Scheer et al. 2021) we analyze its content showing that it contains a big variety of information, inviting further interdisciplinary research.
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The receptionist added me to a group in telegram and the tasks starts from morning 10 am. There were 30+ people like me to perform tasks. We were given a list of tasks to perform and we get money for every 3 tasks. (Screenshot of the earning list attached #3).
The twist comes in at task 9, where they will ask you to put in Rs.1000 and in return they will send you Rs.1200 which is 20% profit, also the promised amount of Rs.240 for Task 7-9. I got alert and started to send private message to the group members that this is a scam and to save their money. To my surprise, I was removed from the group (I guess the few members of the group who I assumed to be like me were scammers themselves). My part in the scam was OVER.
I learnt this from research that these scammers use pump and dump strategy on illiquid crypto currencies and make big money. The scammers are the initial investors of the crypto and the victims money are used to pump up the price. They sell it on high price, making huge profit, while the victims end up losing all their money.
In January 1917, British cryptographers deciphered a telegram from German Foreign Minister Arthur Zimmermann to the German Minister to Mexico, Heinrich von Eckhardt, offering United States territory to Mexico in return for joining the German cause. This message helped draw the United States into the war and thus changed the course of history. Read more...
The Zimmermann Telegram on DocsTeach asks students to analyze the telegram to determine if the United States should have entered World War I based on the telegram's information and implications.
Between 1914 and the spring of 1917, the European nations engaged in a conflict that became known as World War I. While armies moved across the face of Europe, the United States remained neutral. In 1916 Woodrow Wilson was reelected President for a second term, largely because of the slogan "He kept us out of war."
Events in early 1917 would change that hope. In frustration over the effective British naval blockade, Germany broke its pledge to limit submarine warfare on February 1, 1917. In response to the breaking of the Sussex pledge, the United States severed diplomatic relations with Germany. Several weeks later, on February 24, the British presented the Zimmermann telegram to the U.S. Government in an effort to capitalize on growing anti-German sentiment in the United States. The American press published news of the telegram on March 1. On April 6, 1917, the United States Congress formally declared war on Germany and its allies.
The Zimmermann Telegram had such an impact on American opinion that, according to David Kahn, author of The Codebreakers, "No other single cryptanalysis has had such enormous consequences." It is his opinion that "never before or since has so much turned upon the solution of a secret message.
The register, which allowed the public to see checks written to vendors like insurance companies and infrastructure contractors, and included sortable data like court judgments, is too much of a liability for fraud, Batista said.
In the intervening years, many towns large and small have also posted their information online, and the state, at the behest of lawmakers, posts similar information as well as detailed information about salaries paid to public employees.
A spokesperson for Batista did not directly answer a statement about whether it could direct the T&G to other cities in the state that have removed such data. Batista in his statement provided a link to a story about a municipal water treatment facility in Pennsylvania that was hacked due to its use of Israeli components."
Harmful actors use an ever-expanding range of digital spaces to spread harmful ideologies and undermine human rights and democracy online. Understanding their evolving ideas, online networks and activities is critical to developing a more comprehensive evidence base to inform effective and proportional efforts to counter them. But creating that evidence base can challenge the technical capabilities, resources, and even ethical and legal boundaries of research. We are concerned that all these may be getting worse, just as the options for spreading harm online increase. It should therefore be of concern that in many instances it is increasingly hard to conduct digital research in a systematic, ethical and legal manner. This results in a situation where difficult trade offs have to be made between competing goods, including the desire to understand and mitigate harmful content and behaviour online, the preservation of privacy and the adherence to legal agreements. We argue in this report that this does not need to be the case; solutions are available, and actions should be taken as soon as possible to ensure that future researchers have the tools to monitor, track and analyse harmful content and behaviour in the manners outlines (systematically, legally and ethically). This report outlines the findings from the research phase of a project by ISD and CASM Technology, and funded by Omidyar Network. The aim of the project is to identify and test research methodologies to monitor and analyse small, closed or hardly moderated platforms. It provides applied examples and evidence for the limitations and dilemmas encountered by researchers. In three small research case studies, focusing on Telegram, Discord and Odysee in German, English and French respectively, we seek to apply different methodological approaches to analyse platforms that primarily present technological, ethical and legal, or fragmentation barriers.
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