Social networking mood recognition algorithm for conflict detection and management of Indian educational institutions
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ORIGINAL ARTICLE
Social networking mood recognition algorithm for conflict detection and management of Indian educational institutions Sarthak Sengupta1 · Anurika Vaish1 Received: 5 April 2020 / Revised: 24 August 2020 / Accepted: 7 October 2020 © Springer-Verlag GmbH Austria, part of Springer Nature 2020
Abstract Conflict detection and management is a much-needed strategy in educational institutions nowadays. The frequency of clashes, protests, strikes and agitations is rising at an alarming level, particularly with the extensive usage of information and communication technology. This unprecedented issue has cobblestone the research problem and the objective of this study. In order to ensure detection of conflicts using a modified Naïve Bayes algorithm that would assess the sentiments and mood recognition from the tweets of the stakeholders with respect to trends leading to clashes, protests, strikes and agitations existing within the educational environment. Consequently, continuous monitoring and surveillance of the social networking platform have been made to understand the mood recognition and assessment from real-time tweets published on Twitter that would be streamed through Twitter Application Program Interface over the user-given text that would serve as an input for developing early conflict detection strategies. Moreover, Stanford parser has been used to extract keywords that would subsequently be deployed over the tweets for the mood detection module to evaluate the keywords using the preprocessed dictionary. Here, the mood detection module extracts various mood states from the given chorus that supplements the current prevailing sentiments of the stakeholders in academic institutions. This extraction would result in devising strategic formulation and implementation of remedial measures for resolving the unrest in an environment. This would culminate in a healthy educational environment that would ultimately result in overall growth, development, harmony and prosperity of the institutions. Keywords Educational technology · Conflict detection · Social media · Mood recognition · Naïve Bayes · Twitter
1 Introduction Educational institutions are nowadays suffering mostly with the problems of strikes and agitations owing to advancements in technologies such that proper development of the educational institution is getting affected. The stakeholders of the educational institutions are the primary entities who face the consequences of this impact. Stakeholders of the Electronic supplementary material The online version of this article (https://doi.org/10.1007/s13278-020-00701-3) contains supplementary material, which is available to authorized users. * Sarthak Sengupta [email protected] Anurika Vaish [email protected] 1
Department of Management Studies (DOMS), Indian Institute of Information Technology, Allahabad, India
educational institutions mainly comprise of students, teachers, administration, parents and other persons related to the organization externally or internally. In Indian edu
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