E-Business and Social Networks: Tapping Dynamic Niche Markets Using Language-Action and Artificial Intelligence

In this paper, we explore how various social networking platforms currently support the spread of misinformation. We then examine the potential of a few specific multiagent trust modeling algorithms from artificial intelligence, towards detecting that misinformation. Our investigation reveals that specific requirements of each environment may require distinct solutions for the processing. This then leads to a higher-level proposal for the actions to be taken in order to judge trustworthiness. Our final reflection concerns what information should be provided to users, once there are suspected misleading posts. Our aim is to enlighten both the organizations that host social networking and the users of those platforms, and to promote steps forward for more pro-social behaviour in these environments. As a look to the future and the growing need to address this vital topic, we reflect as well on two related topics of possible interest: the case of older adult users and the potential to track misinformation through dedicated data science studies, of particular use for healthcare.

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From the Golem's Jewish Myth to IBM's responsive Watson: where are we going?

Circumscribere International Journal for the History of Science ◽

10.23925/1980-7651.2018v21;p118-122 ◽

2018 ◽

Vol 21 ◽

pp. 118

Author(s):

Jose Luiz Goldfarb ◽

Odecio Souza

Keyword(s):

Artificial Intelligence ◽

Data Mining ◽

Social Networks ◽

21St Century ◽

Collective Intelligence ◽

Spike Jonze

Since data mining uses notions from areas such as cybernetics and artificial intelligence, it is worth evoking here ages-old fears elicited by the idea of automatons created to help humans, but which eventually turned against their creators. Examples might range from the Jewish myth of the Golem to the more famous Frankenstein, Hal from Stanley Kubrick’s 2001: A Space Odyssey (1968), and the more recent Her, by Spike Jonze (2013). In this discussion we pay special attention to the fact that in the 21st-century it seems to be less a matter of creating an individual cybernetic creature, than of the rise of social networks, which are alluded by many as collective intelligence. Such collective intelligence might involve, for instance, the responsive ability of IBM’s Watson.

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Reports on the 2013 AAAI Fall Symposium Series

AI Magazine ◽

10.1609/aimag.v35i2.2538 ◽

2014 ◽

Vol 35 (2) ◽

pp. 69-74

Author(s):

Gully Burns ◽

Yolanda Gil ◽

Yan Liu ◽

Natalia Villanueva-Rosales ◽

Sebastian Risi ◽

...

Keyword(s):

Artificial Intelligence ◽

Neural Networks ◽

Social Networks ◽

Big Data ◽

Computational Social Science ◽

Social Contagion ◽

Washington Dc ◽

Web Analytics ◽

Symbolic Representations ◽

Symposium Series

The Association for the Advancement of Artificial Intelligence was pleased to present the 2013 Fall Symposium Series, held Friday through Sunday, November 15–17, at the Westin Arlington Gateway in Arlington, Virginia near Washington DC USA. The titles of the five symposia were as follows: Discovery Informatics: AI Takes a Science-Centered View on Big Data (FS-13-01); How Should Intelligence be Abstracted in AI Research: MDPs, Symbolic Representations, Artificial Neural Networks, or — ? (FS-13-02); Integrated Cognition (FS-13-03); Semantics for Big Data (FS-13-04); and Social Networks and Social Contagion: Web Analytics and Computational Social Science (FS-13-05). The highlights of each symposium are presented in this report.

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Investigations through the virtual platforms of institutions that develop biomaterials and their relationship with sustainability

Cuadernos del Centro de Estudios de Diseño y Comunicación ◽

10.18682/cdc.vi140.5105 ◽

2021 ◽

Author(s):

Marcelo Vicente Da S. Júnior ◽

Theska Laila De F. Soares ◽

Amilton José Vieira de Arruda

Keyword(s):

Artificial Intelligence ◽

Social Networks ◽

Geographic Origin ◽

New Materials ◽

Biological Origin

Recently, many companies and academic laboratories have emerged formulating new materials of biological origin for use in artifacts, in response to a scenario of unsustainability. This work aimed to investigate institutions that developed biomaterials, focusing on those that had real applications. In this sense, through social networks, several representative examples of the theme were found and analyzed from a qualitative perspective. In addition to an analysis of data collected through images and texts published on these platforms, it was also possible to map other data such as geographic origin, reach and engagement of the analyzed institutions. The results indicate that Instagram’s artificial intelligence was valid to suggest different profiles that had to do with the research, such virtual platforms facilitate the perception and faster visualization of these biomaterials, however for a deeper analysis it was not so efficient, although they serve to disseminate and stimulate new initiatives in this context.

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Co-authorship prediction in academic social network

10.5753/brasnam.2016.6445 ◽

2019 ◽

Cited By ~ 1

Author(s):

William Takahiro Maruyama ◽

Luciano Antonio Digiampietri

Keyword(s):

Artificial Intelligence ◽

Social Networks ◽

Social Network ◽

State Of The Art ◽

The State ◽

Artificial Intelligence Techniques ◽

Academic Social Network ◽

Academic Social Networks

The prediction of relationships in a social network is a complex and extremely useful task to enhance or maximize collaborations by indicating the most promising partnerships. In academic social networks, prediction of relationships is typically used to try to identify potential partners in the development of a project and/or co-authors for publishing papers. This paper presents an approach to predict coauthorships combining artificial intelligence techniques with the state-of-the-art metrics for link predicting in social networks.

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Automated News in Brazilian television: a case study on the AIDA system (Globo-Brazil)

Doxa Comunicación Revista interdisciplinar de estudios de comunicación y ciencias sociales ◽

10.31921/doxacom.n29a13 ◽

2019 ◽

pp. 255-274

Author(s):

Renato Essenfelder ◽

João Canavilhas ◽

Haline Costa Maia ◽

Ricardo Jorge Pinto

Keyword(s):

Artificial Intelligence ◽

Social Networks ◽

Economic Crisis ◽

Competitive Environment ◽

Mainstream Media ◽

Television Network ◽

Secondary Role ◽

Media Ecosystem ◽

The Media

Technological advancements have created a media ecosystem in which traditional journalism sees its existence strongly threatened by the emergence of new players. Social networks have created a competitive environment that, whether due to its dispersion or its capillarity, has relegated the mainstream media to a secondary role in the media ecosystem. Ironically, the technologies that threaten traditional journalism are also those that can save it; provided they are used correctly. Journalism, weakened by the economic crisis and with increasingly smaller newsrooms, has artificial intelligence as an opportunity to recover a certain centrality in the media ecosystem. This paper studies AIDA, a project from the Brazilian television network Globo. This project looked to automation as a way to avoid errors and ambiguities in the news. The study of the AIDA case, complemented by interviews, presents the challenges to achieve the automatization of news regarding electoral polls.

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Sztuczna inteligencja – wybór orzecznictwa

10.13166/wsge/hr-pl/mbtu5710 ◽

2021 ◽

pp. 355-368

Author(s):

Witold Wyporek

Keyword(s):

Artificial Intelligence ◽

Social Networks ◽

Game Design ◽

Human Interaction ◽

Case Review ◽

Security Enhancement ◽

Artificial Intelligence Technology ◽

Medical Radiology ◽

Biometrics Recognition ◽

Technological World

This article represents an overview of the jurisprudence case review of issues relatively connected with artificial intelligence technology. The collection of judgments chosen for the purposes of study which include concerns related to issues associated with forthcoming technological world. For example, the functionality of bot software automate human interaction easy with various online activities, the use of AI to analyse the car cost repairing according to model. AI used in forensic medical radiology, figure print scanning, security enhancement using facial biometrics recognition. AI in automate graphics and game design application. Also AI use to filter social networks to identify inciting terrorism. The main purpose of the study is to identify and assess the need of regulate artificial intelligence technology according to standardize policy, as well as to assess the level of threats associated with privacy of data analysis functions of the AI technology in the context of the presented jurisprudence.

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