Social impact and social media analysis relating to big data

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43310%2F16%3A43913113" target="_blank" >RIV/62156489:43310/16:43913113 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1007/978-3-319-31861-5_13" target="_blank" >https://doi.org/10.1007/978-3-319-31861-5_13</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-31861-5_13" target="_blank" >10.1007/978-3-319-31861-5_13</a>

Result language

angličtina

Original language name

Social impact and social media analysis relating to big data

Original language description

Social media is a component of a larger dynamic and complex media and information domain. As the connection with Big Data grows, its impact in the social media domain cannot be avoided. It is vital that while the positive impact needs to be recognized, the negative impact emerging from Big Data analysis as a social computational tool needs to be recognized and responded to by various agencies. There have been major investments in the development of more powerful digital infrastructure and tools to tackle new and more complex and interdisciplinary research challenges. While there is a need to size the opportunities offered by continuing advances in computational techniques for analyzing social media, the effective use of human expertise cannot be ignored. Using the right data, in the right way and for the right reasons, can change lives for the better, especially if Big Data is used discriminately and transparently. This chapter analyzes the impact of Big Data from social media platforms in the social, political, and economic spheres. Further, the discriminate use of Big Data analysis from social media platforms is explored, within the context of ethical conduct by potential users and proposes important imperatives to minimize, if not control, the negative impact of Big Data analysis from a social perspective.

Czech name

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Czech description

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Type

C - Chapter in a specialist book

CEP classification

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OECD FORD branch

50401 - Sociology

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2016

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Book/collection name

Data Science and Big Data Computing: Frameworks and Methodologies

ISBN

978-3-319-31859-2

Number of pages of the result

21

Pages from-to

293-313

Number of pages of the book

319

Publisher name

Springer Switzerland

Place of publication

Cham

UT code for WoS chapter

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