Nearly 80% of Maryam Nawaz’s Twitter account is made up of bots, fake accounts
Breaking the key figures down, the thread highlighted that out of a total of 5,592,493 followers on her Twitter account, it can be observed that approximately 1 million accounts have no followers whatsoever, 743,906 accounts have only a single follower, and 1,439,946 accounts have between 2 to 5 followers; which leaves approximately 2,408,000 followers that could potentially be termed as partially organic in nature.
This indicates that these accounts are either recently made, or are not being effectively used to reach out and interact with the wider community. As the thread points out by dissecting the age of the accounts, 1898 accounts were created on the day this analysis was conducted (24th September), 37,204 accounts were created a day prior, and 297,537 accounts were created throughout the remainder of September. The assertion that these accounts could have been made recently, can be deemed to be accurate, as thousands of accounts have been systematically generated on a daily basis.
In terms of the organic online activity of these alleged bot accounts, it can be observed from the thread that 2,031,918 accounts have yet to post a single tweet, 685,416 accounts posted only a single tweet, and 1,006,024 accounts have posted between 2 to 5 tweets in total. This is entirely reflective of the fact that a large chunk of these accounts are inorganic, and have only been used to “like” and “retweet” Maryam Nawaz’s activity on the platform, and to artificially inflate her growing number of followers.
The thread concludes that 76% of Maryam Nawaz’s followers on Twitter comprise of fake bot accounts, all of which are used to artificially generate online traction around the politician - adding that out of her approximately 5.5 million followers, 5.19 million have never “liked” or “retweeted” her tweets, indicating that these accounts could be dormant.
According to an independent Karachi-based data scientist, it can be observed through this data analysis that “the levels of engagement are quite low”, and that building an army of online bots is meant to act as “more of an ego boost” which “doesn’t really translate into much online” - citing his prior work on online bot networks, which revealed that “a heavy volume of nodes (people) have either 0 or 1 connections - for the PML-N accounts”.
When asked if these online bots can be geo-located, reported and shut down, he added that most bot accounts do not accurately share their locations, if they are part of a “bot farm” (or a collective of fake accounts operating in tandem), the platform’s algorithm can detect and remove them accordingly. It was also mentioned that online Twitter audit tools are “not accurate”, and that they only use a limited dataset (of 5000 followers) to make relevant assertions, adding that a broad array of variables (including account creation date, number of followers, accounts being followed, etc.) are necessary to attain a richer and comprehensive analysis.
In the aftermath of the 2016 U.S Presidential election and the Brexit vote, in which online bot-activity played an unprecedented role in the spread of online misinformation and being used as a tool to gain online political clout, Twitter has been clamping down aggressively on any bot-activity, but its algorithm can not effectively keep up the pace against an army of online bots numbering in the hundreds of thousands.
Brecoder
- An online analysis of Maryam Nawaz’s Twitter account has revealed that behind the politician’s massive online clout, there is serious evidence to suggest that it is the result of a systematic use of online bot accounts (or fake accounts).
Breaking the key figures down, the thread highlighted that out of a total of 5,592,493 followers on her Twitter account, it can be observed that approximately 1 million accounts have no followers whatsoever, 743,906 accounts have only a single follower, and 1,439,946 accounts have between 2 to 5 followers; which leaves approximately 2,408,000 followers that could potentially be termed as partially organic in nature.
This indicates that these accounts are either recently made, or are not being effectively used to reach out and interact with the wider community. As the thread points out by dissecting the age of the accounts, 1898 accounts were created on the day this analysis was conducted (24th September), 37,204 accounts were created a day prior, and 297,537 accounts were created throughout the remainder of September. The assertion that these accounts could have been made recently, can be deemed to be accurate, as thousands of accounts have been systematically generated on a daily basis.
In terms of the organic online activity of these alleged bot accounts, it can be observed from the thread that 2,031,918 accounts have yet to post a single tweet, 685,416 accounts posted only a single tweet, and 1,006,024 accounts have posted between 2 to 5 tweets in total. This is entirely reflective of the fact that a large chunk of these accounts are inorganic, and have only been used to “like” and “retweet” Maryam Nawaz’s activity on the platform, and to artificially inflate her growing number of followers.
The thread concludes that 76% of Maryam Nawaz’s followers on Twitter comprise of fake bot accounts, all of which are used to artificially generate online traction around the politician - adding that out of her approximately 5.5 million followers, 5.19 million have never “liked” or “retweeted” her tweets, indicating that these accounts could be dormant.
According to an independent Karachi-based data scientist, it can be observed through this data analysis that “the levels of engagement are quite low”, and that building an army of online bots is meant to act as “more of an ego boost” which “doesn’t really translate into much online” - citing his prior work on online bot networks, which revealed that “a heavy volume of nodes (people) have either 0 or 1 connections - for the PML-N accounts”.
When asked if these online bots can be geo-located, reported and shut down, he added that most bot accounts do not accurately share their locations, if they are part of a “bot farm” (or a collective of fake accounts operating in tandem), the platform’s algorithm can detect and remove them accordingly. It was also mentioned that online Twitter audit tools are “not accurate”, and that they only use a limited dataset (of 5000 followers) to make relevant assertions, adding that a broad array of variables (including account creation date, number of followers, accounts being followed, etc.) are necessary to attain a richer and comprehensive analysis.
In the aftermath of the 2016 U.S Presidential election and the Brexit vote, in which online bot-activity played an unprecedented role in the spread of online misinformation and being used as a tool to gain online political clout, Twitter has been clamping down aggressively on any bot-activity, but its algorithm can not effectively keep up the pace against an army of online bots numbering in the hundreds of thousands.
Brecoder
