its accuracy, is highly popular and endorsed by many, exerting an influence against which we haven’t yet developed antibodies. Our vulnerability makes it possible for a bot to acquire significant influence, even unintentionally. 2 Sophisticated bots can generate personas that appear as credible followers, and thus are more difficult for both people and filtering algorithms to detect. They make for valuable entities on the fake follower market, and allegations of acquisition of fake followers have touched several prominent political figures in the U.S. and worldwide.

Journalists, analysts, and researchers increasingly report more examples of the potential dangers brought by social bots. These include the unwarranted consequences that the widespread diffusion of bots may have on the stability of markets. There have been claims that Twitter signals can be leveraged to predict the stock market, 5 and there is an increasing amount of evidence showing that market operators pay attention and react promptly to information from social media. On April 23, 2013, for example, the Syrian Electronic Army hacked the Twitter account of the Associated Press and posted a false rumor about a terror attack on the White House in which President Obama was allegedly injured. This provoked an immediate crash in the stock market. On May 6, 2010 a flash crash occurred in the U.S. stock market, when the Dow Jones plunged over 1,000 points (about 9%) within minutes—the biggest one-day point decline in history. After a five-month-long investigation, the role of high-frequency trading bots became obvious, but it yet remains unclear whether these bots had access to information from the social Web. 22

The combination of social bots
with an increasing reliance on auto-
matic trading systems that, at least
partially, exploit information from so-
cial media, is ripe with risks. Bots can
amplify the visibility of misleading
information, while automatic trading
systems lack fact-checking capabili-
ties. A recent orchestrated bot cam-
paign successfully created the appear-
ance of a sustained discussion about a
tech company called Cynk. Automatic
trading algorithms picked up this con-
versation and started trading heavily
in the company’s stocks. This resulted
in a 200-fold increase in market value,
bringing the company’s worth to $5
billion.b By the time analysts recog-
nized the orchestration behind this
operation and stock trading was sus-
pended, the losses were real.

The Bot Effect

These anecdotes illustrate the conse-
quences that tampering with the so-
cial Web may have for our increasingly
interconnected society. In addition to
potentially endangering democracy,
causing panic during emergencies,
and affecting the stock market, so-
cial bots can harm our society in even
subtler ways. A recent study demon-
strated the vulnerability of social me-
dia users to a social botnet designed
to expose private information, like
phone numbers and addresses. 7 This
kind of vulnerability can be exploited
by cybercrime and cause the erosion
of trust in social media. 22 Bots can
also hinder the advancement of pub-
lic policy by creating the impression
of a grassroots movement of con-
trarians, or contribute to the strong
polarization of political discussion
observed in social media. 12 They can
alter the perception of social media
influence, artificially enlarging the
audience of some people, 14 or they
can ruin the reputation of a com-
pany, for commercial or political
purposes. 25 A recent study demon-
strated that emotions are contagious
on social media23: elusive bots could
easily infiltrate a population of un-
aware humans and manipulate them
to affect their perception of reality,
with unpredictable results. Indirect
social and economic effects of social
bot activity include the alteration of
social media analytics, adopted for
various purposes such as TV ratings,c
expert findings, 40 and scientific im-
pact measurement.d
b The Curious Case of Cynk, an Abandoned
Tech Company Now Worth $5 Billion; mash-
able.com/2014/07/10/cynk
c Nielsen’s New Twitter TV Ratings Are a To-
tal Scam. Here’s Why; defamer.gawker.com/
nielsens-new-twitter-tv-ratings-are-a-total-
scam-here-1442214842

d altmetrics: a manifesto; altmetrics.org/mani-festo/

Act Like a Human, Think Like a Bot One of the greatest challenges for bot detection in social media is in understanding what modern social bots can do. 6 Early bots mainly performed one type of activity: posting content automatically. These bots were naive and easy to spot by trivial detection strategies, such as focusing on high volume of content generation. In 2011, James Caverlee’s team at Texas A&M University implemented a honeypot trap that managed to detect thousands of social bots. 24 The idea was simple and effective: the team created a few Twitter accounts (bots) whose role was solely to create nonsensical tweets with gibberish content, in which no human would ever be interested. However, these accounts attracted many followers. Further inspection confirmed that the suspicious followers were indeed social bots trying to grow their social circles by blindly following random accounts.

In recent years, Twitter bots have become increasingly sophisticated, making their detection more difficult. The boundary between human-like and bot-like behavior is now fuzzier. For example, social bots can search the Web for information and media to fill their profiles, and post collected material at predetermined times, emulating the human temporal signature of content production and consumption—including circadian patterns of daily activity and temporal spikes of information generation. 19 They can even engage in more complex types of interactions, such as entertaining conversations with other people, commenting on their posts, and answering their questions. 22 Some bots specifically aim to achieve greater influence by gathering new followers and expanding their social circles; they can search the social network for popular and influential people and follow them or capture their attention by sending them inquiries, in the hope to be noticed. 2 To acquire visibility, they can infiltrate popular discussions, generating topically appropriate—and even potentially interesting— content, by identifying relevant keywords and searching online for information fitting that conversation. 17 After the