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                <text>Book Chapter</text>
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    <name>Book Chapter</name>
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          <name>Title</name>
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              <text>Stakeholders' expressions of tech layoffs: A text mining analysis on the "Balance of Arguments"</text>
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              <text>The volume and nature of work undertaken by the tech employees is humongous, tech employees are known to manage those high tides because of attractive salary packages, perks, and other incentive options, which turn out to be a catastrophic collapse when such layoffs are levied, giving little or no room for a quick transfer to another job from the viewpoint of the affected employees. User-generated unstructured data content in the forms of either tweets, reviews, or comments from around seven major social media platforms were collected to understand the various expressions and discussions linked to layoffs. The collected data is further segregated into employee expressions, social media reviewers, news critiques views, etc., and their perspectives were further analysed. The overall analysis of sentiments on various stakeholders are formulated using Python (Juypter Notebook) package. The authors attempt to model out the viewpoints of various expressors and suggests various measures to be taken by the tech majors to better handle the phenomenon of layoffs.  2023, IGI Global. All rights reserved.</text>
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          <name>Creator</name>
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              <text>Kalyani V.; Praveen B.P.; Pradeep M.</text>
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              <text>HR Analytics in an Era of Rapid Automation, pp. 54-63.</text>
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              <text>IGI Global</text>
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              <text>2023-01-01</text>
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              <text>&lt;a href="https://doi.org/10.4018/978-1-6684-8942-0.ch004" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.4018/978-1-6684-8942-0.ch004&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169528753&amp;amp;doi=10.4018%2F978-1-6684-8942-0.ch004&amp;amp;partnerID=40&amp;amp;md5=da71ecdde6ae7e5a5c040c57ac659dfe" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169528753&amp;amp;doi=10.4018%2f978-1-6684-8942-0.ch004&amp;amp;partnerID=40&amp;amp;md5=da71ecdde6ae7e5a5c040c57ac659dfe&lt;/a&gt;</text>
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              <text>Restricted Access</text>
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              <text>ISBN: 978-166848944-4; 978-166848942-0</text>
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              <text>Online</text>
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              <text>English</text>
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              <text>Kalyani V., CHRIST University, India; Praveen B.P., CHRIST University, India; Pradeep M., KPIT Technologies GmbH, Germany</text>
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