The extensive use of social media has tremendous impact on culture, business, and politics on the world at large with potentially positive and negative effects. For example, social media coverage of crisis events may be used by authorities for effective disaster management or by malicious entities to spread rumors and fake news for financial or political benefit. Considering the harmful consequences of fake news in social media, there is a profound need to detect false information, control and/or prevent it from spreading. In this paper, we propose an advanced framework to identify tweets with fake news contents using techniques including statistical analysis of Twitter user account, reverse image searching, cross verification of fake news sources, and data mining. Experimental results on a large miscellaneous events dataset demonstrate the effectiveness of our proposed approach in identifying fake tweets.

In 2018, as part of its attempts to rid its platform of misinformation, Twitter removed more than 70 million fake accounts, dealing a significant blow to fake profile operators. More recently, Twitter's been working on a new bot labeling system, which would help users better understand which profiles are real people and which are not, while this month, Twitter also announced an update to its Developer API policy which specifically rules that:

"...developers clearly indicate (in their account bio or profile) if they are operating a bot account, what the account is, and who the person behind it is, so it’s easier for everyone on Twitter to know what’s a bot - and what’s not."  

So, Twitter now has an official rule in place to call out bots, and eliminate bot networks for those that fail to comply. And this latest bot network discovery shows that it absolutely needs to enforce this, and take action against bots and fake profiles in order to stop mass-manipulation campaigns, and limit their potential influence, especially with respect to political initiatives.

It may well be, too, that the COVID-19 pandemic could play a part in this. Like all platforms, Twitter is working hard to detect and remove coronavirus misinformation, which is a crucial element in the battle against the spread of the virus. People need accurate, timely information and updates, and in its efforts to combat such, maybe Twitter is learning more about the networks behind these campaigns, and how it can refine its systems to better detect them and reduce their impact. 

The COVID-19 pandemic has highlighted, more than ever, the key role that social platforms now play in providing information to the public, and with that, maybe we'll see more action taken across the board to eliminate all forms of manipulative behavior, reducing its impacts. 

We can only hope that Twitter is able to take more action on such - because while Twitter doesn't have as many users as Facebook, it's still highly influential. Twitter is the real-time news source of choice for many passionate newshounds and community leaders, and they take what they find and share it with their networks everywhere else. As highlighted by the Leeds hospital story, these bot pushes spread, and their influence stretches well beyond Twitter itself.

You can also check this website to generate fake tweets:- Fake Tweet Generator

Even if you don't use Twitter, and you don't feel like such campaigns impact you and your opinions, they likely do, as they eventually trickle through to all corners of the web.

Twitter, of course, has various issues to deal with right now as it works to meet rising demand, while dealing with its own staffing impacts as a result of the COVID-19 lockdowns. But in the wake of this, Twitter needs to take more action to address its bot issues.