editedbook
Publication: IIP Proceedings Year: 2022, Month: November Page No: 95-103, ISSN/ISBN: 978-93-95632-69-0, DOI/Link: https://www.rsquarel.org/assets/docupload/rsl20232C1AE4344826FAF.pdf
A FRAMEWORK OF MEDIA METRICS DESIGNED ON INTERNET OF THINGS
Area/Stream: IOT, Authors: Dr. Pallavi Mishra Keywords: Media measurement, Machinetype communication, IoT application, Smart media. Book Name /series: Futuristic Trends in IOT, Volume 2, Book 15, Part 2, Chapter 3Publication: IIP Proceedings Year: 2022, Month: November Page No: 95-103, ISSN/ISBN: 978-93-95632-69-0, DOI/Link: https://www.rsquarel.org/assets/docupload/rsl20232C1AE4344826FAF.pdf
Abstract:
With the spread of internet and the emergence of diverse smart devices along with a plethora of media applications, the media measurement and monitoring system have witnessed a paradigm shift. Gradually new technologies have a strong influence on the market forces and given a new way to media metrics. The metrics and methods applied to measure the popularity index of old form of media is completely different from the new form of online news monitoring system. Internet of things have designed a framework of analytical tools, methods, and metrics that identify the impact factor of new media ecosystem by analyzing media impact measurement. It is also important to emphasize that the focus here is on more recent changes in methods of measurement to media metrics, although it doesn’t encompass readership, circulation or TRP rather reflects the impression. The current static and portable-based audience rating measuring techniques are rarely being used to evaluate the media metrics. A plethora of interdisciplinary methods encapsulating data mining, text mining, social network analysis, trend analysis, and sentiment analysis. In this chapter, we put forth the idea of a Machine-type Media Measurement System, which can cite and visualize media measurement data using Machine-type People Meters and Big Data platforms. Through a dispersed M2M network, this system may gather information from users about their media usage. The measure like online viewership and circulation are not the major forces of popularity index because these don’t exist in cyber world. The services such as ComScore and Alexa developed methods to measure traffic on web sites. Thus, this paper seeks to identify relevant analytical approaches, methodologies, and metrics for assessing media impact in the age of online media. The metrics like online viewing and circulation aren't the main drivers of the popularity index. Methods for measuring website traffic have been developed by businesses like ComScore and Alexa. Therefore, the purpose of this chapter is to establish pertinent analytical strategies, frameworks, and metrics for measuring media impact in the era of online media.
Cite this: Dr. Pallavi Mishra,"A FRAMEWORK OF MEDIA METRICS DESIGNED ON INTERNET OF THINGS", Futuristic Trends in IOT, Volume 2, Book 15, Part 2, Chapter 3, November, 2022, 95-103, 978-93-95632-69-0, https://www.rsquarel.org/assets/docupload/rsl20232C1AE4344826FAF.pdf
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