A mathematical model designed by data analytics company GlobalData has estimated that around 10% of Twitter’s active accounts are posting spam Content. The company noted that this was double that of Twitter’s reported figure — likely due to a difference in criteria as to what counts as ‘spam’.
Sidharth Kumar, Senior Data Scientist at GlobalData, comments, “What is or is not spam is suddenly an important discussion point for the social media platform, given that Elon Musk’s bid to take over Twitter is now on hold due to a disagreement on the proportion of spam accounts on the platform. Twitter claims that bot/spam accounts on Twitter represent less than 5% of accounts while Elon Musk’s team thinks otherwise.
“The precise proportion of spam accounts is difficult to compute, as it is almost impossible to confirm the identity of the entity behind a tweet handle. Additionally, the definition of a ‘spam account may differ for everyone. Incessant tweeting of non-original content can be considered spam, but some may choose to see it as a very active user sharing articles/opinions.”
Keeping all this in mind, GlobalData’s mathematical model estimated the number of spam accounts using multiple parameters to provide a weighted score, which was then used to determine the classification of ‘spam’ or ‘non-spam’. GlobalData decided on these parameters by focusing on the differences in activity between typical spam accounts and that of an average Twitter user. Accounts performing poorly on many parameters received a higher score, indicating a higher probability of being spam. GlobalData analysts then independently observed handles at different score levels, and decided the cutoff for the classification (‘spam’ or ‘non-spam’) by consensus. Some of the parameters used in the model were as follows:
- Is the tweet handle verified?
- Is a tweet coming from third-party avenues?
- What is the number of historic Tweets that the handle has produced, divided by the days since its creation?
Image credit: GlobalData
