Thursday, October 20, 2016
Tweets His Own
One of the interesting political tracking metrics follows activity on various social networks. Not only do Web-trackers measure volumes of postings on social media – linking those bursts with parallel real-time events – but they also have the ability to look at tone and valance of the postings. In short, they have automated software that can identify the sentiments expressed on social media (positive, negative or neutral) almost in real time. This analytical process goes along with those instantaneous “vote online” polls where consumers express their individual preferences based on such late-breaking news or political event (like the presidential debates).
Then the desperate 24/7/365 newscasters lap up the results in their fearsome pursuit of (a) “news” material and (b) indices of who is ahead. There is truth in that information… as well as an opportunity for crass manipulation. You’ve all seen those little “I am not a robot” tests when you are giving an opinion or “sharing” a news story online. Well, while that is well and good for the sites that deploy use these verification techniques, there are lots of folks who don’t. If you were linked to Twitter and following Donald Trump, you might be aware that during Trump’s real-time, on-camera participation in the presidential debates, Trump tweets were flowing. Hmmmm?
So in jolly old Brexited England, Oxford University, under the watchful eye of Professor Philip Howard, decided to see how those automated robotic postings (bots) were impacting those massive online/mobile buzz and communications, what the experts call the “computational propaganda.” Given Donald’s Trump’s addiction to Twitter, not shared by his Democratic opponent, the interest in tracking that particular social media site was obvious. The October 18th BBC.com reports: “More than four times as many tweets were made by automated accounts in favour of Donald Trump around the first US presidential debate as by those backing Hillary Clinton, a study says.
“The bots , it suggests, but Trump would still have won a higher number of supportive tweets even if they had not.
“The authors warn such software has the capacity to ‘manipulate public opinion’ and ‘muddy political issues.’…The report has yet to be peer-reviewed… And one critic noted that it was impossible to be completely sure which accounts were real and which were ‘web robots.’” Twitter is easier to analyze, and its use of hashtags increases the level of impersonal anonymity, easy pickings for bot-driven manipulation. And the hashtags that represented pro-Clinton (e.g., #dirtydonald or#strongertogether) and pro-Trump (e.g., #deplorable or #neverhillary) were pretty easy to categorize.
You know a social medium is way too common when the expression has moved from an upper case, “Tweet,” to a vernacular lower case “tweet.” So Professor Howard and his crew focused on the September 26 U.S. presidential debate (plus three days) and the resulting Twitter traffic. In sheer numbers, Trump dominated the Tweet-o-sphere. “These [hashtags that clearly were pro one candidate or another] accounted for about 1.8 million pro-Trump tweets and 613,000 pro-Clinton posts.
“The researchers then analysed which of these had been posted by bots. They identified an account as such if it had tweeted at least 50 times a day across the period, meaning a minimum of 200 tweets over the four days… The results suggested that 32.7% of such pro-Trump tweets had been posted by bots and 22.3% of such pro-Clinton ones… In total, that represented a total of 576,178 tweets benefiting the Republican nominee and 136,639 in support of the Democratic one.” BBC.com. Turns out that Trumps tweets, whatever the source, were also more effective than those of HRC. He is exceptionally adept at social media and has used this métier like the media professional he truly is. After the next debate, Professor Howard’s study showed a significant upsurge of robo-tweets from the Clinton campaign.
But the question of the reliability of social media tracking is increasingly complicated by automated plants. As these automated systems gain sophistication, especially with growing artificial intelligence, bots are able to analyze photographs and apply a much higher level of linguistic capacity to short circuit those “I am not a robot” tests, making tracking veracity decreasingly reliable. The Oxford study suggested that the implications beyond political campaigns also raise serious questions, especially on Twitter:
“Looking wider - to accounts that tweeted neutral hashtags or a mix of different kinds - the study suggested that 23% of all the tweets were driven by bots… One machine learning expert cautions that the criteria used to identify the bots might have been too imprecise to have sifted out all the human-based activity.
“‘Real people can write a script and use an algorithm to tweet regularly with specific responses, or humans can tweet content that looks almost identical to a series of bots flooding a political hashtag,’ comments Caroline Sinders, an ex-IBM researcher who now works for Buzzfeed… ‘Also, political commentators or people eagerly engaged in the political debate could also tweet this many times.’
“So, is it possible that Trump supporters might simply have been more enthusiastic than Clinton's and have done a better job at leveraging social media to their advantage?... Prof Howard said that it is unlikely to be the only explanation.
“‘Most of the heavy automation and tweets happened overnight and shared similar hashtags and information,’ he explains… ‘They show behaviour that is not human and often don't have comments [about other issues apart from] the particular topic in question.’” BBC.com. Whatever the reason, we need to have healthy skepticism when accepting reports of such social media aggregations as a true representation of public opinion. There are too many of us ready to believe whatever we are told electronically and digitally, without investigating the true source of the online expression.
I’m Peter Dekom, and a notion of what is true and what is falsely planted by those with an agenda requires that we constantly ask who is expressing which opinion and why.