Internet Bots Research Articles

A videoconferencing verification method for enrollment of breastfeeding dyads to an online prospective mixed methods study during the COVID-19 pandemic.

To apply videoconferencing as a new verification method prior to enrollment for an online survey-based study. A prospective-observational, mixed methods, three group, repeated measures study involved recruiting a population-based sample of breastfeeding mothers and infants (N = 81). Twenty-seven mothers were recruited for each group: mothers returning to work outside of the home, mothers returning to work from home and mothers staying home with their infants full-time. Data were collected at four time points, infant age 4, 12, 20 and 24 weeks, via online survey. Participating mothers received a $10 gift card for completing each survey. Social media, word of mouth and brochures promoted United States-based recruitment nationwide. A publicly available direct link to the survey was initially provided to interested mothers. After the suspicion of online fraud, videoconferencing was instituted for self-referrals and phone calls for professional referrals. The survey was invaded by response fraud 3 weeks after the initial survey deployment. Out of 109 respondents who visited the survey site during that timeframe, only eight mothers (10%) were eligible (22 June 2022 to 14 July 2022). After recruitment modification, 313 individuals emailed the study team with 65 self-referred mothers (80%) enrolled in the study via videoconferencing while eight mothers (10%) had a professional referral and enrolled via phone call (23 August 2022 to 30 March 2023). Providing a direct survey link, even with CAPTCHA-protection, evoked fraudulent responses. Videoconferencing is an emerging verification method that can be readily applied to the enrollment of breastfeeding dyads for an online study. The emergence of fraudulent respondents and internet bots threatens data quality. This study addressed the strategy of videoconferencing as a new verification method for recruitment and enrollment of breastfeeding dyads. This knowledge can be applied by researchers to secure sample validity and data integrity.

Internet-Based Mental Health Survey Research: Navigating Internet Bots on Reddit

This study was a multistage process of recruiting participants through Reddit with the intent of increasing data integrity when facing an infiltration of Internet bots. Approaches to increase data integrity centered around preventing the occurrence of Internet bots from the onset and increasing the ability to identify Internet bot responses. We attempted to detect bots in a study focused on understanding social factors related to autism and suicide risk. Four recruitment rounds occurred through Reddit on mental health-related subreddits, with one post made on each subreddit per recruitment round. We found high presence of bots in the initial rounds-indeed, using location data, one third of the total responses (33.4 percent; 118/353) came from just eight locations (i.e., 4.7 percent of all locations). The proportion of detected bots was significantly different across the rounds of recruitment (χ2 = 150.22, df = 3, p < 0.001). In round 4, language advertising compensation was removed from recruitment posts. This round had significantly lower proportions of detected bots compared with round 1 (χ2 = 33.01, df = 1, p < 0.001), round 2 (χ2 = 129.14, df = 1, p < 0.001), and round 3 (χ2 = 46.6, df = 1, p < 0.001). Through a multistage recruitment process, we were able to increase the integrity of our collected data, as determined by a low percentage of fraudulent responses. Only once we removed advertisement of compensation in recruitment posts, did we see a significant decrease in the quantity and percentage of Internet bot responses. This multistage recruitment study provides valuable information regarding how to adapt when an online survey study is infiltrated with Internet bots.

Methodological Challenge: Addressing Bots in Online Research

Internet-based research has become useful for data collection, particularly because it reduces the time and resources required for recruitment. Although participant recruitment using social media is a scientifically and ethically sound methodology for many studies, this approach attracts fraudulent participants and Internet bots which can pose serious threats to sample validity and data integrity. We present several case examples of research studies in which bots were encountered and the procedures used to address them. In addition, we provide an overview of strategies researchers can use to mitigate the risks associated with Internet-based recruitment methods.

Social media networks, fake news, and polarization

We study how the structure of social media networks and the presence of fake news affects the degree of misinformation and polarization in a society. For that, we analyze a dynamic model of opinion exchange in which individuals have imperfect information about the true state of the world and exhibit bounded rationality. Key to the analysis is the presence of internet bots: agents in the network that spread fake news (e.g., a constant flow of biased information). We characterize how agents’ opinions evolve over time and evaluate the determinants of long-run misinformation and polarization in the network. To that end, we construct a synthetic network calibrated to Twitter and simulate the information exchange process over a long horizon to quantify the bots’ ability to spread fake news. A key insight is that significant misinformation and polarization arise in networks in which only 15% of agents believe fake news to be true, indicating that network externality effects are quantitatively important. Higher bot centrality typically increases polarization and lowers misinformation. When one bot is more influential than the other (asymmetric centrality), polarization is reduced but misinformation grows, as opinions become closer the more influential bot’s preferred point. Finally, we show that threshold rules tend to reduce polarization and misinformation. This is because, as long as agents also have access to unbiased sources of information, threshold rules actually limit the influence of bots.

Assessing intolerance, the level of protest on the internet and the impact of botfarms on political life in modern France from a sociological standpoint

The relevance of the stated research subject is conditioned upon the fact that the rapid development of Internet technologies has established conditions for the self-organisation of the population and the development of an entirely new quality of citizens’ participation in the political process in democratic countries. It is particularly reflected in the emergence of protest movements, which in the modern world are marked by a lack of clearly defined leaders and a horizontal organisational structure. The purpose of this research is to assess the level of protest sentiment on the Internet in contemporary France, the impact of bot activities on social and political life in the country and the development of political activism. The author applied a set of general scientific and specific research methods to solve the objectives identified. The structural-functional method provided the foundation for a study of the impact of modern information and communication technologies on French political life against the backdrop of the “yellow vests” protests. In addition, the author used systemic, comparative, socio-psychological and institutional methods. The results of the study should be considered as determining the role of social media and other platforms in the rise of protest sentiments in France and assessing manifestations of intolerance in the French segment of the Internet. Particular attention was devoted to the activities of botfarms and their influence in “warming up” the protest and destabilising the socio-political situation. The results of this research have significance for political forces that target the consolidation of the electorate by using information and communication technologies and using the online environment to mobilise society and engage citizens more broadly in protest actions. In addition, the author considered the activity of Internet bots as a tool to influence society in a democratic country and a method of fighting in the information war

Internet-Based Mental Health Survey Research: Navigating Internet Bots on Reddit

Internet-Based Mental Health Survey Research: Navigating Internet Bots on Reddit

Ensuring survey research data integrity in the era of internet bots.

We used an internet-based survey platform to conduct a cross-sectional survey regarding the impact of COVID-19 on the LGBTQ + population in the United States. While this method of data collection was quick and inexpensive, the data collected required extensive cleaning due to the infiltration of bots. Based on this experience, we provide recommendations for ensuring data integrity. Recruitment conducted between May 7 and 8, 2020 resulted in an initial sample of 1251 responses. The Qualtrics survey was disseminated via social media and professional association listservs. After noticing data discrepancies, research staff developed a rigorous data cleaning protocol. A second wave of recruitment was conducted on June 11–12, 2020 using the original recruitment methods. The five-step data cleaning protocol led to the removal of 773 (61.8%) surveys from the initial dataset, resulting in a sample of 478 participants in the first wave of data collection. The protocol led to the removal of 46 (31.9%) surveys from the second two-day wave of data collection, resulting in a sample of 98 participants in the second wave of data collection. After verifying the two-day pilot process was effective at screening for bots, the survey was reopened for a third wave of data collection resulting in a total of 709 responses, which were identified as an additional 514 (72.5%) valid participants and led to the removal of an additional 194 (27.4%) possible bots. The final analytic sample consists of 1090 participants. Although a useful and efficient research tool, especially among hard-to-reach populations, internet-based research is vulnerable to bots and mischievous responders, despite survey platforms’ built-in protections. Beyond the depletion of research funds, bot infiltration threatens data integrity and may disproportionately harm research with marginalized populations. Based on our experience, we recommend the use of strategies such as qualitative questions, duplicate demographic questions, and incentive raffles to reduce likelihood of mischievous respondents. These protections can be undertaken to ensure data integrity and facilitate research on vulnerable populations.

На что способны боты? (Модель протестной и контрпротестной политической мобилизации)

Despite the increasing interest among scholars in the effect of Internet bots, or automated social media accounts, on the processes of political communication and mobilization in the online sphere, the extent of bots’ effectiveness and the specific mechanisms of their use remain largely understudied. The deficit of the overarching conceptual understanding and concrete results is arguably due to researchers’ aspiration to solve a problem in the empirical way, without attempting to combine data analysis with mathematical and computational modeling. Having analyzed the existing models on the topic, the authors offer their own model that is based on the spiral-of-silence theory. The key features of the model that set it apart from the existing ones are the following: a) taking into account differences in the types of motivation and costs associated with expressing protest and loyalist sentiments; b) including “partner effect” into the spiral-ofsilence mechanism; c) employing a neurological decision-ma king scheme according to which the same stimulus can prompt action and be a deterrent. On the basis of a series of computational experiments with the model, the authors demonstrate that bots are more effective in mobilizing opposition members when an individual motivated for political participation refrains from it because his local social community does not share his views. In this case, the emergence of a like-minded partner bot can destroy the spiral of silence created by this community and encourage this individual to openly express his position. On the contrary, when mobilizing loyalists, bots are most effective in relation to poorly motivated individuals. The model elaborated by the authors not only allows us to evaluate bots’ effects in a new way, but it also sheds light on how people make decisions in the framework of political communication and mobilization in social networks.

The Connotation, Features, and Mechanism of Computational Propaganda

The purpose of the work is to identify the connotation, features of computational propaganda and reveal how computational propaganda uses new technologies to manipulate public opinion.&#x0D; The study’s hypothesis is the assumption that computational propaganda, as a new type of propaganda and manipulation of public opinion spawned in the era of artificial intelligence, stealthily and massively steers public opinion using new technologies to influence political and social processes.&#x0D; With the scientific methods such as event analysis and case-study, the work concludes that more and more governments, political parties, and strategic communication companies use social media as the digital platform, Internet bots as the automated executors, and algorithms as the computational technical guarantee, by participating in, guiding and creating controversial topics and events, to manipulate public opinion and win international competitions, policy debates, elections, etc.

Abstract PS7-44: Energetics and lifestyle in inherited syndromes (ELLIE'S study)

Abstract Background: US women have a 1 in 8 lifetime chance of developing breast cancer (BC), with an estimated 10% resulting from a hereditary BC gene mutation. Individuals with mutations in genes such as BRCA1 and BRCA2 have an increased risk of breast and ovarian cancer, as well as other types of cancers. At present, there are more than a dozen other hereditary cancer related genetic mutations that have an associated moderate to high risk of developing cancer. Along with an ability to identify and characterize risk in individuals with a hereditary cancer mutation, there is a need to study modifiable factors such as dietary intake and physical activity in relation to an individual’s risk for cancer. Obesity and poor physical fitness are independently associated with an increased risk of BC and recurrence. There is a paucity of data on the impact of BMI, obesity, and physical activity on primary and recurrent BC in genetic mutation carriers. Women with a moderate penetrance gene mutation are at a high risk for BC and yet are likely to have an impact from modifiable risk factors. The impact of obesity, diet, and physical activity on BC risk and outcomes needs to be further characterized in genetic mutation carriers. Methods: A short REDCap electronic survey was disseminated on social media and through our advocate partner Facing our Risk of Cancer Empowered (FORCE). Eligible participants include males or females, ≥18 years with a hereditary cancer genetic mutation. The survey includes questions regarding personal health, weight, height, metabolic risk factors, reproductive history as well as personal and/or family history of cancer and gene mutation status. In addition, includes a standardized assessment for diet (14-Item Mediterranean Diet Tool) and physical activity (IPAQ and modifiable PAQ). The first 1000 participants are compensated for their time with a $10 e-card. The survey is available in English and Spanish. The Spanish version was developed in collaboration with JUNTOS Kansas City. Objectives: To establish a cohort and describe obesity rates, physical activity, metabolic factors, and nutrition in a cohort of individuals that have an increased risk of cancer due to a hereditary cancer genetic mutation. Results: A total of N = 1,117 surveys have been completed as of June 30, 2020. Of them, 61.2% were removed from final analysis due to incomplete surveys, internet bots, and multiple single-user entries. A total N = 443 surveys have been verified and included in this analysis. Demographics: 98.6% female (n= 437), 94.4% white (n = 418) and median age 46 (range 19 – 77 yrs). Mutations represented in the cohort include: BRCA2 (39.0%), BRCA1 (29.1%), CHEK2 (13.1%), and ATM (5.9%) and &amp;lt; 5%: PALB2, RAD51D, and TP53. Median BMI 24.9 ± 6.06 stdv. BMI 25 to &amp;lt; 30: 26.4% (n = 117). BMI 30 or &amp;gt; 30: 23.47% (n = 104). 61.3% responders are currently trying to lose weight. Attempts at weight loss: No attempts: n = 60 (13.5%), at least 1: n = 55 (12.4%), 2-5: n = 211 (47.6%), 6 or more: n = 117 (26.4%). Limitations to exercise include motivation (26.9%), time (23.5%), not liking exercise (15.6%), and lack of gym memberships (12.4%). 74.9% (n = 332) responded that they are interested in participating in future studies. The Spanish survey was made available 3/3/2020, no responses to date. Conclusion: Individuals harboring a hereditary cancer genetic mutation are interested and willing to participate in research focused on lifestyle modifications and association with cancer risk. Rates of being overweight or obese are high and many have made multiple attempts at weight loss and find common barriers to exercise. Social media is a feasible platform to recruit to a lifestyle research project in a rare population. Additional steps to limit internet trolls, bots, and repetitive responses are necessary but did not impede recruitment. Further effort and collaboration are needed to expand the survey to underrepresented minorities. Citation Format: Lauren E Nye, Kendra Cruz, Sue Friedman, Diane Rose, Christie Befort, Debra K Sullivan, Jill M Hamilton-Reeves, Lisa M Harlan-Williams, Fariba Behbod, Jo Wick, Melinda Irwin, Jennifer Klemp. Energetics and lifestyle in inherited syndromes (ELLIE'S study) [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS7-44.

Dynamic pricing with automated purchase-reservation algorithms

We consider the problem of a firm that sells a perishable product such as airline tickets or hotel rooms with a dynamic pricing scheme in the presence of Internet bots. The bots automatically check for changes in the selling price every few seconds and hold the price for a short period by making a tentative reservation. Since the bots are not willing to buy the product, the bots’ reservation does not generate revenue for the firm. In addition, such a behavior would temporarily increase the price in conjunction with decreasing the inventory level. In this paper, we formulate a dynamic pricing model that accounts for tentative reservations made by bots, and derive an optimal pricing policy so as to maximize the total expected revenue. We show the monotone properties of the optimal price: (1) the optimal price decreases with inventory at any given timestep; (2) the optimal price decreases over time even if there is a temporary inventory decrease due to bot reservations. We demonstrate numerically that the optimal pricing policy is robust against the presence of bots, and further show that, as bot activity increases, the optimal price tends to decrease in the first portion of the sales interval.

Automating fandom: Social bots, music celebrity, and identity online

In an analysis of the intersection of media and politics through the increased presence of social bots on social media platforms like Twitter, it becomes evident that years before internet bots were used for geopolitical cyberconflict, fan communities online were already subject to these forces in driving user engagement for music brands and celebrities. Fan scholars must interrogate the presence of these bot networks for their impact on online fan cultural activity.

SpiderTrap—An Innovative Approach to Analyze Activity of Internet Bots on a Website

The main idea behind creating SpiderTrap was to build a website that can track how Internet bots crawl it. To track bots, honeypot dynamically generates different types of the hyperlinks on the web pages leading from one article to another and logs information passed by web clients in HTTP requests when visiting these links. By analyzing the sequences of visited links and passed HTTP requests it is possible to: detect bots, reveal bots' crawling or scanning algorithms, and other characteristic features of the traffic they generate. In our research we focused on identifying and describing whole bots' operations rather than just classifying single HTTP requests. This novel approach has given us insight into what different types of Internet bots are looking for and how they work. This information can be used to optimize the websites for search engines' bots for a better place on a search's results page or prepare a set of rules for tools that filter traffic to the web pages to minimize the impact of bad and unwanted bots on the websites' availability and security. We present the results of the five months of SpiderTrap's activity when honeypot was accessible by two domains (.pl and.eu), as well as by an IP address. The results show examples of activity of well-known Internet bots, such as Googlebot or Bingbot, unknown crawlers, and scanners trying to exploit vulnerabilities in the most popular web frameworks or looking for active webshells (i.e. access points to control a web server left by other attackers).

Political Conflicts around the Internet in Russia: The Case of Yandex.Novosti

Between 2014 and 2016 the news aggregator Yandex.Novosti was at the core of a political conflict between the internet company Yandex and state authorities in Russia. The Yandex algorithm, conceived and developed to select and publish online news, was suspected of political bias by the Russian authorities in the context of the Ukrainian crisis.Russian legislators engaged in a two year controversy in order to control the algorithm through its registration under the law on mass media. Since 2016 the Yandex.Novosti bot is legally responsible for the content it publishes, as with other mass media. Analysis of this conflict offers the opportunity to show the new political stakes and strategies surrounding internet bots in Russia. In the critical sociology of science and technology,Western scholars have worried about the undemocratic effects of algorithms and software governing the internet. Lawrence Lessig expressed this concern with his famous sentence “code is law,” arguing for the public regulation of code in order to protect the constitutional rights of citizens. In the Russian context, on the contrary, public regulation of the code by state authorities is considered a new attack against press freedom and democracy by defenders of the “bot.” The code is considered the main defender of citizens’ rights against the state. This controversy shows the specificity of political stakes concerning the “Runet” (Russian internet) and the necessity to shift interpretative frames on the internet depending on national context. DOI: 10.25285/2078–1938–2017–9–2–112–132

A Novel CAPTCHA Design Approach using Boolean Algebra

CAPTCHAs are employed on web systems for strengthen web security to protect from internet bots, fraudulent registration, spammers. So CAPTCHA is designed in such a way the patterns display on CAPTCHA feature that human can easily pass but hardship for automated approaches. Usability and security are two rudimental issues for CAPTCHA design and implementation. In Math calculus CAPTCHA test that be inherent with trigonometric and differential functions. Due to complexity of equations, user cannot easily solve expressions that possess poor usability of CAPTCHA. In this paper, a novel CAPTCHA design approach using Boolean algebra is present, to improve usability and security as contrast to Math calculus CAPTCHA. In this approach, logic gates will be design that depict shapes like OR, AND, NOR, NAND, NOR, etc. by use online digital library tool. Each gate executes a Boolean expression as represent by shape indicating operation. The shapes relate to the logic gates like conjunction, disjunction and complement. To prove human, user will identify shape of given logic gates and choose correct option that display in form of Boolean algebra for pass CAPTCHA test. From security issue, Boolean algebra CAPTCHA is non OCR based that provide no development in advance technologies like AI and automated software.

Recommendations for Future Development of Artificial Agents [Commentary

A set of technologies, loosely referred to as “artificial agents,” is becoming more pervasive and more powerful in the current computing landscape. All artificial agents are built on a computational foundation. Some are purely computational, e.g., Internet bots, search engines, and others are physically embodied entities with computational decision-making components, e.g., robots, unmanned aerial vehicles (UAVs), and autonomous cars. The noteworthy feature of artificial agents - the feature that leads to the artificial agent label - is their capacity to operate autonomously. At some level or to some degree, artificial agents operate independently from the humans who design and deploy them. They are agents in the sense that we deploy them to perform tasks on our behalf and often these tasks involve learning and decision-making. Since humans previously performed many of these tasks, we mark the difference, that is, the machine performance of these tasks, by referring to them as “artificial.