What types of COVID-19 conspiracies are populated by Twitter bots?

“tc.). The presence of bots has been documented in the context of online political discussion [1]–[3], public health [4]–[8], civil unrest [9], stock market manipulation [10], the spread of false news [11]–[13], alongside with other tools such as troll accounts [5], [6], [14]–[17]. In this paper, we chart the landscape…”

“tion on February 11, 2020) were reported in Wuhan, China in late December 2019; the first fatalities were reported in early 2020. The first case in the United States was announced on January 21, 2020 [18]: our Twitter data collection aligns with that date [19]. The fast-rising infection rates and death toll led the Ch…”

“On a different note, [23] looked at social media sentiment as expression of potential mental health issues associated with social isolation and other side-effects of containment measures enacted to limit the spread of COVID-19 in China.”

“ve a digital trail associated with the data center used to dispatch tweets. RQ2: CHARACTERIZING BOT FUELED CAMPAIGNS Data-driven computational sensemaking can fail when using human communication data [66]. Common reasons include population and sampling bias, platform-design bias, distortion of human and nonhuman behav…”

“[74] M.”

“The literature on bot detection has become very extensive [31], [36], [49]–[51].”

“[12] N.”

“The work by Pennycook and colleagues epitomizes the seriousness of this problem by showing, with a social experiment including 1,600 participants, that subjects tend to share misinformation and false claims about COVID-19 predominantly because they are unable to determine whether the content is scientifically sound an…”

“According to work by [5], [42], similar conclusions can be drawn for bots active in public health discussions, with the intent to spread claims contrary to scientific evidence.”

“ed by the activity of automated accounts, often referred to as bots (a.k.a., social bots, sybil accounts, etc.). The presence of bots has been documented in the context of online political discussion [1]–[3], public health [4]–[8], civil unrest [9], stock market manipulation [10], the spread of false news [11]–[13], a…”

“(1) Botometer3, also used here, is a bot-detection tool developed at Indiana University [52]; (2) BotSlayer4 is an application to detect and track potential manipulation of information on Twitter; (3) the Bot Repository5 is a centralized database to share annotated datasets of Twitter bots.”

“idation section. The spread of conspiracies on online social media is a well-established issue. Numerous studies have been devoted to understand, for example, how unscientific claims circulate online [71]–[74], or how conspiratorial narratives are constructed online [75]–[77], especially in the context of political id…”

“nly observing a small fraction, approximately 1%, of the overall Twitter conversation, through the lens of the Twitter API. This has been shown to introduce some biases toward over-represented topics [87], and COVID-19 has been the most spoken-about topic of discussion ever since the beginning of the pandemic. Second,…”

“ation and sampling bias, platform-design bias, distortion of human and nonhuman behavior, multiple hypotheses and comparisons testing, and more, which can hamper computational models and bias results [67]. An hybrid approach based on combining computational analysis and human validation has been called for in order to…”

“[72] A.”

“oted to understand, for example, how unscientific claims circulate online [71]–[74], or how conspiratorial narratives are constructed online [75]–[77], especially in the context of political ideology [2], [78]. Our analysis highlights the emergence of similar issues in the context of the conversation related to COVID-…”

“centralized database to share annotated datasets of Twitter bots. Finally, various models have been proposed to detect bots using sophisticated machine learning techniques, such as: (1) Deep learning [53], (2) Anomaly detection [54]–[57], (3) Time series analysis [38], [58], [59]. Due to the continuously evolving natu…”

“en referred to as bots (a.k.a., social bots, sybil accounts, etc.). The presence of bots has been documented in the context of online political discussion [1]–[3], public health [4]–[8], civil unrest [9], stock market manipulation [10], the spread of false news [11]–[13], alongside with other tools such as troll accou…”

“[4] V.”

“esearch Projects Agency) aimed at detecting bots used for anti-science misinformation [4]. More recently, large bot networks (botnets) have been discovered on Twitter by various research groups [43], [44], [46], [48]. The literature on bot detection has become very extensive [31], [36], [49]–[51]. In [31], we proposed…”

“nced Research Projects Agency) aimed at detecting bots used for anti-science misinformation [4]. More recently, large bot networks (botnets) have been discovered on Twitter by various research groups [43], [44], [46], [48]. The literature on bot detection has become very extensive [31], [36], [49]–[51]. In [31], we pr…”

“e identification of highly-predictive features that discriminate between bots and humans. Other recent surveys propose complementary or alternative taxonomies that are worth considering as well [36], [50], [51] Some openly accessible tools exist to detect bots on platforms like Twitter: (1) Botometer3, also used here,…”

“An hybrid approach based on combining computational analysis and human validation has been called for in order to make sense of massive-scale communication datasets [68], [69].”

“r further details. Bot behavior research. Numerous studies have been devoted to characterize the behavior of bots [36]– [38] and the ethical issues pertaining their use [39]. E.g.: According to [30], [40], [41], the behavior of political bots can be categorized with respect to their goals: • Manufacturing consensus, t…”

“inuum of behavior along the dimensions of social media engagement is also in line with two other theories, namely the notions of “super-participation” [61] and that of “dynamical classes of behavior” [62]. In our case, we adopt the same idea to segmenting the dimension of human-to-bot likeness and dividing the continu…”

“[15] A.”

“[73] D.”

“is a well-established issue. Numerous studies have been devoted to understand, for example, how unscientific claims circulate online [71]–[74], or how conspiratorial narratives are constructed online [75]–[77], especially in the context of political ideology [2], [78]. Our analysis highlights the emergence of similar…”

“35] for further details. Bot behavior research. Numerous studies have been devoted to characterize the behavior of bots [36]– [38] and the ethical issues pertaining their use [39]. E.g.: According to [30], [40], [41], the behavior of political bots can be categorized with respect to their goals: • Manufacturing consen…”

“Bots have been categorized according to various taxonomies [29], [30].”

“odels and bias results [67]. An hybrid approach based on combining computational analysis and human validation has been called for in order to make sense of massive-scale communication datasets [68], [69]. Content sensemaking. In this section, we address RQ2 using content and timeseries analysis techniques, in combina…”

“ch social media. The work by Singh and colleagues also looked at the spatio-temporal dynamics of misinformation spread on Twitter, drawing a picture with similar implications as the two studies above [26]. More research is needed, as the information landscape evolves, and more scientific insights are unveiled on the c…”

“ng bots appears to dissipate toward the end of our observation window (early March). This type of bot behavior has been documented already in the past, and is commonly related to as “trend hijacking” [85], [86]: bots appear to ride the wave of popularity of a given topic, in this case the trending COVID-19 discussion,…”

“[45] Y.”

“The presence of bots has been documented in the context of online political discussion [1]–[3], public health [4]–[8], civil unrest [9], stock market manipulation [10], the spread of false news [11]–[13], alongside with other tools such as troll accounts [5], [6], [14]–[17].”

“As of the time of this writing (mid-April 2020), the vast majority of these studies are pre-print papers that provide a timely, yet partial, characterization of online discussion and issues revolving around COVID-19 [19]–[28].”

“The idea that there exists a continuum of behavior along the dimensions of social media engagement is also in line with two other theories, namely the notions of “super-participation” [61] and that of “dynamical classes of behavior” [62].”

“tweet text alongside with the URL. The large majority of the observed news bots tweets have been captured because the headlines contain one of the keywords used to seed the real-time data collection [19]. DISCUSSION COVID-19 is a global crisis and with people being pushed out of physical spaces due to containment meas…”

“h Projects Agency) aimed at detecting bots used for anti-science misinformation [4]. More recently, large bot networks (botnets) have been discovered on Twitter by various research groups [43], [44], [46], [48]. The literature on bot detection has become very extensive [31], [36], [49]–[51]. In [31], we proposed a sim…”

“Numerous studies have been devoted to understand, for example, how unscientific claims circulate online [71]–[74], or how conspiratorial narratives are constructed online [75]–[77], especially in the context of political ideology [2], [78].”

“The presence of bots has been documented in the context of online political discussion [1]–[3], public health [4]–[8], civil unrest [9], stock market manipulation [10], the spread of false news [11]–[13], alongside with other tools such as troll accounts [5], [6], [14]–[17].”

“[59] D.”

“[7] T.”

“[37] L.”

“[16] A.”

“[56] Z.”

“y an alleged "deep state" against U.S. President Donald Trump and his supporters”. QAnon has been extensively adopted by alt-right activists to foster participatory advocacy on social media [79], but it has also been abused by the Russian Internet Research Agency (IRA) to push conspiratorial and divisive nar…”

“well-established issue. Numerous studies have been devoted to understand, for example, how unscientific claims circulate online [71]–[74], or how conspiratorial narratives are constructed online [75]–[77], especially in the context of political ideology [2], [78]. Our analysis highlights the emergence of similar issue…”

“[34] E.”

“[88] E.”

“[76] A.”

“[84] D.”

“The presence of bots has been documented in the context of online political discussion [1]–[3], public health [4]–[8], civil unrest [9], stock market manipulation [10], the spread of false news [11]–[13], alongside with other tools such as troll accounts [5], [6], [14]–[17].”

“to determine whether the content is scientifically sound and accurate or not [22]. Other studies investigated collective attention and engagement dynamics concerning COVID-19 on Twitter. For example, [20] analyzed 1,000 unigrams (1-grams) posted on Twitter in 24 languages during early 2020, and compared them with the…”

“(1) Deep learning [53], (2) Anomaly detection [54]–[57], (3) Time series analysis [38], [58], [59].”

“e annotated datasets of Twitter bots. Finally, various models have been proposed to detect bots using sophisticated machine learning techniques, such as: (1) Deep learning [53], (2) Anomaly detection [54]–[57], (3) Time series analysis [38], [58], [59]. Due to the continuously evolving nature of bots, and the challeng…”

“s appears to dissipate toward the end of our observation window (early March). This type of bot behavior has been documented already in the past, and is commonly related to as “trend hijacking” [85], [86]: bots appear to ride the wave of popularity of a given topic, in this case the trending COVID-19 discussion, to in…”

“ects Agency) aimed at detecting bots used for anti-science misinformation [4]. More recently, large bot networks (botnets) have been discovered on Twitter by various research groups [43], [44], [46], [48]. The literature on bot detection has become very extensive [31], [36], [49]–[51]. In [31], we proposed a simple ta…”

“The presence of bots has been documented in the context of online political discussion [1]–[3], public health [4]–[8], civil unrest [9], stock market manipulation [10], the spread of false news [11]–[13], alongside with other tools such as troll accounts [5], [6], [14]–[17].”

“Numerous studies have been devoted to characterize the behavior of bots [36]– [38] and the ethical issues pertaining their use [39].”

“[80] G.”

“Numerous studies have been devoted to characterize the behavior of bots [36]– [38] and the ethical issues pertaining their use [39].”

“, GreatAwakening, Inf0wars, WWGWGA (Where We Go One We Go All), WeThePeople, and PatriotsFights [82].”

“[70] F.”

“nline political discussion [1]–[3], public health [4]–[8], civil unrest [9], stock market manipulation [10], the spread of false news [11]–[13], alongside with other tools such as troll accounts [5], [6], [14]–[17]. In this paper, we chart the landscape of Twitter chatter within the context of COVID-19 related convers…”

“Similar approaches have been developed in the domain of information warfare detection: one such example, is the CUT (Commenting User Typology) Framework, which was proposed to classify comment abuse, where users are divided into quadrants of behaviors alongside various dimensions of interest [60].”

“algorithmic manipulation, to trick recommendation and ranking systems used by social media platforms, and give higher visibility to certain actors, viewpoints, or campaigns. According to work by [5], [42], similar conclusions can be drawn for bots active in public health discussions, with the intent to spread claims c…”

“t-right activists to foster participatory advocacy on social media [79], but it has also been abused by the Russian Internet Research Agency (IRA) to push conspiratorial and divisive narratives [80], [81]. QAnon appears alongside with other known alt-right terms, e.g., GreatAwakening, Inf0wars, WWGWGA (Where We Go One…”

“nt, or clonedcontent from other users; finally, (7) pausing activity to mimic human circadian cycles and bursty behaviors, as well as to satisfy API constraints, and to avoid suspension. According to [35], these features can enable bots to carry out various forms of abuse including: denigrate and smear, deceive and ma…”

“In an analysis of 43 million COVID-19–related tweets, bots were found to be pushing a number of conspiracy theories, such as QAnon, in addition to retweeting links from partisan news sites [73].”

“Bots also actively participate in public health debates [12] including those about vaccines [13, 14], the COVID-19 pandemic [15, 16, 17, 18], and cannabis [19].”

“Therefore, similar to previous work [23,26,28], we binned users by evenly distributed deciles of the polarity scores, with each decile containing exactly 10% of all users.”