One of the favorite topics among supporters of Donald Trump, the Republican candidate in the US presidential election, is the larger number of his supporters on social media compared to his Democratic rival, Hillary Clinton. Last week, a conservative Trump supporter told CNN that it only seems that Trump has fewer supporters than Hillary in older media (like television) and phone polls. However, if you look at social media platforms like Facebook or Twitter, Trump supporters are three times more than Clinton's. But is this claim accurate? According to The Atlantic magazine, as the role of social media becomes more prominent in people's lives, election campaigns are now using other tools to attract audiences. One of these tools is active bots on these networks. These bots create artificial traffic for these candidates on social media. A recent study conducted by Oxford University shows that between the last two televised debates between these two rivals, more than one-third of tweets supporting Donald Trump were generated by Twitter bots. This figure is one-fifth for Hillary Clinton's campaign. These results align with a report published earlier by Vanity Fair, which stated that most supporters of these two campaigns on social media come from automated (bot) accounts. While technology enthusiasts and futurists advocate for technologies that can instantly verify the statements of these representatives or access their history on various issues through internet searches, the dangers that these technologies pose to public opinion formation cannot be overlooked. Creating a Twitter bot is very easy, and many hate groups, such as white supremacists or opponents of same-sex relationships, use them to create a favorable image of themselves. Online polls can also be very misleading because one person can vote for an option multiple times. This happened after the election debates between Clinton and Trump, where Trump repeatedly claimed he won the post-debate polls. DNA India, in a report related to this, quotes engineers from the University of Southern California, stating that the growth of these Twitter bots has disrupted the discussions related to the US elections in the online world. Emilio Ferraro, one of the researchers at this university, says, "Internet bots, which present themselves with human masks online, have an unprecedented impact on election-related discussions on social media." According to Ferraro, these bots could jeopardize the integrity of the 2016 US elections. The Atlantic states that the increasing presence of these bots on social media is inevitable in the future. However, it is the responsibility of the government, NGOs, and educational and research institutions to design bots that defend citizen power rather than persuade them to vote for a specific candidate.
The Impact of Twitter Bots on the US Elections
The article discusses the influence of Twitter bots on the perception of Donald Trump's support compared to Hillary Clinton in the US elections. A study reveals that a significant portion of tweets supporting Trump were generated by bots, raising concerns about the integrity of online political discourse. This issue highlights the challenges posed by social media in shaping public opinion.
👥 Key Players
📰 What Happened
A study revealed that a significant portion of tweets supporting Donald Trump during the election were generated by Twitter bots, while a smaller percentage supported Hillary Clinton. This raises concerns about the integrity of online political discourse.
- Over one-third of tweets supporting Trump were generated by bots, compared to one-fifth for Clinton.
- The presence of bots in political discussions can mislead public opinion and disrupt election integrity.
💡 Why It Matters
📚 Background
Social media has become a critical platform for political campaigns, influencing public opinion and voter behavior. The rise of automated accounts (bots) complicates this landscape by artificially inflating support for candidates.
🏷️ Entities Mentioned
Translated from the original and edited for English readers. View original source →
Translation confidence: 85%