29,734 research outputs found
Bots increase exposure to negative and inflammatory content in online social systems
Societies are complex systems which tend to polarize into sub-groups of
individuals with dramatically opposite perspectives. This phenomenon is
reflected -- and often amplified -- in online social networks where, however,
humans are no more the only players, and co-exist alongside with social bots,
i.e., software-controlled accounts. Analyzing large-scale social data collected
during the Catalan referendum for independence on October 1, 2017, consisting
of nearly 4 millions Twitter posts generated by almost 1 million users, we
identify the two polarized groups of Independentists and Constitutionalists and
quantify the structural and emotional roles played by social bots. We show that
bots act from peripheral areas of the social system to target influential
humans of both groups, bombarding Independentists with violent contents,
increasing their exposure to negative and inflammatory narratives and
exacerbating social conflict online. Our findings stress the importance of
developing countermeasures to unmask these forms of automated social
manipulation.Comment: 8 pages, 5 figure
Towards Cognitive Bots: Architectural Research Challenges
Software bots operating in multiple virtual digital platforms must understand
the platforms' affordances and behave like human users. Platform affordances or
features differ from one application platform to another or through a life
cycle, requiring such bots to be adaptable. Moreover, bots in such platforms
could cooperate with humans or other software agents for work or to learn
specific behavior patterns. However, present-day bots, particularly chatbots,
other than language processing and prediction, are far from reaching a human
user's behavior level within complex business information systems. They lack
the cognitive capabilities to sense and act in such virtual environments,
rendering their development a challenge to artificial general intelligence
research. In this study, we problematize and investigate assumptions in
conceptualizing software bot architecture by directing attention to significant
architectural research challenges in developing cognitive bots endowed with
complex behavior for operation on information systems. As an outlook, we
propose alternate architectural assumptions to consider in future bot design
and bot development frameworks
Building Decision Adviser Bots
This overview article explores the prospects and promises of new technologies for developing conversational software to aid, assist and advise people in personal and organizational decision situations. The quest for conversational decision advisers began in the 1970s with the development of interactive, computing systems like the Hewlett-Packard 2000 Access Time- Share systems. With the advent of Cloud-based, Artificial Intelligence development environments, the capabilities needed to develop conversational software are increasingly available and easy to use. Hence, it is feasible to develop decision adviser (DA) bots and the bots are easier to deploy. Bots can be built for action taking and for question and answer dialogs. DA bots can be deployed for use in both structured and semi-structured decision situations. DA bots can perform increasingly complex tasks. Overall, more exploratory design science research is needed to improve our understanding of the design, development, and deployment of DA bots for use by managers, customers, and clients
Demystifying Social Bots: On the Intelligence of Automated Social Media Actors
Recently, social bots, (semi-) automatized accounts in social media, gained global attention in the context of public opinion manipulation. Dystopian scenarios like the malicious amplification of topics, the spreading of disinformation, and the manipulation of elections through “opinion machines” created headlines around the globe. As a consequence, much research effort has been put into the classification and detection of social bots. Yet, it is still unclear how easy an average online media user can purchase social bots, which platforms they target, where they originate from, and how sophisticated these bots are. This work provides a much needed new perspective on these questions. By providing insights into the markets of social bots in the clearnet and darknet as well as an exhaustive analysis of freely available software tools for automation during the last decade, we shed light on the availability and capabilities of automated profiles in social media platforms. Our results confirm the increasing importance of social bot technology but also uncover an as yet unknown discrepancy of theoretical and practically achieved artificial intelligence in social bots: while literature reports on a high degree of intelligence for chat bots and assumes the same for social bots, the observed degree of intelligence in social bot implementations is limited. In fact, the overwhelming majority of available services and software are of supportive nature and merely provide modules of automation instead of fully fledged “intelligent” social bots
Bots in software engineering: a systematic mapping study
Bots have emerged from research prototypes to deployable systems due to the recent developments in machine learning, natural language processing and understanding techniques. In software engineering, bots range from simple automated scripts to decision-making autonomous systems. The spectrum of applications of bots in software engineering is so wide and diverse, that a comprehensive overview and categorization of such bots is needed. Existing works considered selective bots to be analyzed and failed to provide the overall picture. Hence it is significant to categorize bots in software engineering through analyzing why, what and how the bots are applied in software engineering. We approach the problem with a systematic mapping study based on the research articles published in this topic. This study focuses on classification of bots used in software engineering, the various dimensions of the characteristics, the more frequently researched area, potential research spaces to be explored and the perception of bots in the developer community. This study aims to provide an introduction and a broad overview of bots used in software engineering. Discussions of the feedback and results from several studies provide interesting insights and prospective future directions
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