Just how full of fakes is Twitter? Photo: Getty
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Why fake Twitter accounts are a political problem

The rise in the use of Twitter bots and automated accounts, particularly by politicians and campaigns, is skewing what we see as trends.

In recent years, the phrase “trending on Twitter” has become shorthand for any issue that’s capturing public interest on a massive scale. Journalists and politicians cite popular hashtags as evidence of grassroots support.

Increasingly, though, this chatter isn’t coming from real people at all. Along with the rise in Twitter use has come a boom in so-called “Twitter bots” – automated accounts whose tweets are generated entirely by computer.

Many users, for example, have been surprised to encounter beautiful women lurking in chat rooms who seem unaccountably keen to discuss porn and recommend their favourite sites. Such bots exist entirely to entice other users to click on promotional links, generating revenue for their controllers.

Some bots are harmless, or even funny: @StealthMountain, for example, automates the pedant in all of us by replying: “I think you mean ‘sneak peek’” to tweets that include the phrase ‘sneak peak’.

It’s not clear just how many of Twitter’s 255m active users are fake – but it’s a lot. According to the company itself, the figure is about five per cent, kept down by a team of 30 people who spend their days weeding out the bots. However, two Italian researchers last year calculated that the true figure was 10 per cent, and other estimates have placed the figure even higher.

Now, researchers at Indiana University have created a new tool, BotOrNot, designed to identify Twitter bots from their patterns of activity.

“Part of the motivation of our research is that we don’t really know how bad the problem is in quantitative terms,” says Professor Fil Menczer, director of the university’s Centre for Complex Networks and Systems Research.

“Are there thousands of social bots? Millions? We know there are lots of bots out there, and many are totally benign. But we also found examples of nasty bots used to mislead, exploit and manipulate discourse with rumors, spam, malware, misinformation, political astroturf and slander.”

BotOrNot analyses over 1,000 features of an account – from its friend network to the content of messages and the times of day they’re sent – to deduce the likelihood that an account is fake, with 95 percent accuracy, says the team.

Meanwhile, a tool developed by social media analytics firm Socialbakers uses similar criteria to discover what percentage of a user’s followers are fake. These include the proportion of followers to followed accounts and the number of retweets and links.

Tools such as these are now starting to quantify a trend noticed by researchers over the last two or three years: the use of bots for political purposes. Having thousands of followers retweeting their every word makes politicians look popular, and can turn a pet cause into a top trend worldwide. The practice is known as astroturfing – the creation of fake grass-roots support.

Three years ago, for example, it was alleged that over 90 per cent of Newt Gingrich’s followers showed all the hallmarks of being fake; more recently, during the 2012 Mexican elections, researchers found that the Institutional Revolutionary Party was using tens of thousands of bots to push its messages onto Twitter’s list of top trends.

This month’s elections in India have attracted their fair share of bot activity, too. During India’s last visit to the polls, only one politician had a Twitter account, boasting just 6,000 followers. This time round, more than 56m election-related tweets were sent between 1 January and polling day on 12 May. During the same period, prime ministerial candidate Narendra Modi boosted his follower count by 28 per cent, hitting nearly four million.

However, according to SocialBakers, all is not what it seems: nearly half Modi’s followers look suspicious. Modi has form here: late last year, when Time started monitoring Twitter for its Person of the Year award, local media soon spotted a pattern. Thousands of Modi’s followers were tweeting “I think Narendra Modi should be #TIMEPOY” at regular intervals, 24 hours a day – while a rival army of bots was tweeting the opposite.

And don't think it can’t happen here. Bots are easily and cheaply bought, with the going rate around a thousand followers for a dollar; more if you want them to like or share your posts. In 2012, Respect candidate for Croyden North Lee Jasper admitted that his by-election campaigners had been using Twitter bots to boost his apparent popularity in the same way: “It’s all part of modern campaigning,” he said.

Meanwhile, applying the SocialBakers tool to leading UK political accounts, it appears that most have a preponderance of genuine followers. One notable exception is @Number10gov, the prime minister's official account: as many as half the followers of this account appear to be bots, with names such as “@vsgaykjppvw”, “@zekumovuvuc” and “@zong4npp”.

Still, it's possible that @Number10gov doesn't mind this too much: the BotOrNot tool calculates there’s a 72 per cent chance that it's a bot itself. Maybe we should just leave them to talk amongst themselves. . .

Joshua M. Jones for Emojipedia
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The emojis proposed for release in 2016 are faintly disturbing

Birds of prey, dead flowers and vomit: Emojipedia's vision for 2016. 

Since, as we're constantly being told, emojis are now the fastest growing languge in the UK, it seems only appropriate that its vocabulary should expand to include more commonly used images or ideas as its popularity increases. 

Next year, the Unicode Consortium, which decides which new codes can be added to the emoji dictionary, will approve a new round of symbols. So far, 38 suggestions have been accepted as candidates for the final selection. Emojipedia, an online emoji resource, has taken it upon itself to mock up the new symbols based on the appearance of existing emojis (though emojis are designed slightly differently by different operating systems like Apple or Android). The full list will be decided by Unicode in mid-2016. 

As it stands, the new selection is a little... well, dark. 

First, there are the faces: a Pinnochio-nosed lying face, a dribbling face, a nauseous face, an upset-looking lady and a horrible swollen clown head: 

Then there's what I like to call the "melancholy nighttime collection", including a bat, owl, fox, blackened heart and dying rose: 

Here we have a few predators, thrown in for good measure, and a stop sign:

There are a few symbols of optimism amid the doom and gloom, including a pair of crossed fingers, clinking champagne glasses and smiling cowboy, plus a groom and prince to round out the bride and princess on current release. (You can see the full list of mock-ups here). But overall, the tone is remarkably sombre. 

Perhaps as emoji become ever more popular as a method of communication, we need to accept that they must represent the world in all its darkness and nuance. Not every experience deserves a smiley face, after all. 

All mock-ups: Emojpedia.

Barbara Speed is a technology and digital culture writer at the New Statesman and a staff writer at CityMetric.