scholarly journals A Review on Epidemiological Methods to Detect Untrue Information

Author(s):  
Akanksha Mathur ◽  
◽  
Prof. C. P. Gupta ◽  

Online propagation of untrue information has been and is becoming an increasing problem. Understanding and modeling the diffusion of information on Online Social Networks (OSN's) of voluminous data is the prime concern. The paper provides the history of the epidemic spread and its analogy with untrue information. This paper provides a review of untrue information on online social networks and methods of detection of untrue information based on epidemiological models. Open research challenges and potential future research directions are also highlighted. The paper aimed at aiding research for the identification of untrue information on OSNs.

Author(s):  
Akanksha Mathur ◽  
◽  
Prof. C. P. Gupta ◽  

Online propagation of untrue information has been and is becoming an increasing problem. Understanding and modeling the diffusion of information on Online Social Networks (OSN's) of voluminous data is the prime concern. The paper provides the history of the epidemic spread and its analogy with untrue information. This paper provides a review of untrue information on online social networks and methods of detection of untrue information based on epidemiological models. Open research challenges and potential future research directions are also highlighted. The paper aimed at aiding research for the identification of untrue information on OSNs.


Author(s):  
Pulkit Mehndiratta

With the ever-increasing acceptance of online social networks (OSNs), a new dimension has evolved for communication amongst humans. OSNs have given us the opportunity to monitor and mine the opinions of a large number of online active populations in real time. Many diverse approaches have been proposed, various datasets have been generated, but there is a need of collective understanding of this area. Researchers are working around the globe to find a pattern to judge the mood of the user; the still serious problem of detection of irony and sarcasm in textual data poses a threat to the accuracy of the techniques evolved till date. This chapter aims to help the reader to think and learn more clearly about the aspects of sentiment analysis, social network analysis, and detection of irony or sarcasm in textual data generated via online social networks. It argues and discusses various techniques and solutions available in literature currently. In the end, the chapter provides some answers to the open-ended question and future research directions related to the analysis of textual data.


Author(s):  
Maria Northcote

The field of online learning, like many other technological innovations, has not burgeoned without controversy. Despite the debates about the role and value of online learning, it has continued to grow in many sectors, especially in higher education. Alongside the growth of online learning, discussions about its benefits and limitations have also flourished, and many studies have investigated the quality and integrity of online courses. This chapter offers an investigation of some of the history of online learning, concluding with a collection of practical recommendations and suggestions for future research directions to guide institutions embarking on online learning programs.


Author(s):  
Steven Walczak

Artificial intelligence is the science of creating intelligent machines. Human intelligence is comprised of numerous pieces of knowledge as well as processes for utilizing this knowledge to solve problems. Artificial intelligence seeks to emulate and surpass human intelligence in problem solving. Current research tends to be focused within narrow, well-defined domains, but new research is looking to expand this to create global intelligence. This chapter seeks to define the various fields that comprise artificial intelligence and look at the history of AI and suggest future research directions.


Author(s):  
Nikolaos Karipidis ◽  
Jim Prentzas

Wiki technology has become very popular during the last years and is used in many fields. It enables the collaborative creation and management of content retaining the history of changes. There is abundant wiki-based content on the web covering a large number of subjects. A significant contribution of wikis involves education. Under certain conditions, technology may enhance the learning process due to the unique features it encompasses. In this context, wikis may prove very helpful as they provide the infrastructure for collaborative learning approaches and the development of online learning communities. This chapter discusses main features of wikis, wiki features specifically required in education, and typical uses of wikis in education. Representative examples of successful wikis are presented. Future research directions are also outlined.


2020 ◽  
pp. 322-330
Author(s):  
Allison Margaret Bigelow

This chapter reviews the major methodological and theoretical approaches used in Mining Language, at once concluding the book and gesturing toward future research directions in the fields of history of colonial science and technology and Indigenous Studies. Specifically, it reflects on the relationship between history and literary studies within these intersecting fields. By reflecting on what colonial archives say and do not say, the conclusion argues for the importance of research ethics and methods that confront, acknowledge, and respond to historical silences.


Author(s):  
Sylvaine Castellano ◽  
Insaf Khelladi

New opportunities and challenges are emerging thanks to the growing Internet importance and social media usage. Although practitioners have already recognized the strategic dimension of e-reputation and the power of social media, academic research is still in its infancy when it comes to e-reputation determinants in a social networks context. A study was conducted in the sports setting to explore the impact of social networks on the sportspeople's e-reputation. Whereas the study emphasized (1) the influence of social networks' perception on the sportspeople's e-reputation, and the neutral roles of (2) the motives for following sportspeople online, and (3) the negative content on the Internet, additional insights are formulated on maintaining, restoring and managing e-reputation on social networks. Finally, future research directions are suggested on the role of image to control e-reputation.


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