Evaluation of Opinions of Individuals about Various Technical and Non-Technical Events
Khushdeep Kaur1, Mohammad Shabaz2

1Khushdeep Kaur, Department of Computer Science Engineering, Universal Institute of Engineering & Technology, Mohali (Punjab), India.
2Mohammad Shabaz, Department of Computer Science Engineering, Universal Institute of Engineering & Technology, Mohali (Punjab), India.
Manuscript received on 07 April 2019 | Revised Manuscript received on 20 April 2019 | Manuscript published on 30 April 2019 | PP: 162-164 | Volume-8 Issue-6, April 2019 | Retrieval Number: F3607048619/19©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Sentimental analysis is an easiest way to find out the different opinions of various people about their reaction after attending any event.The boom of sentimental analysis extends up to finding the real time emotions of an individual which can be obtained based on the data generating during various technical or non-technical events. Generally, the obtained data is categorized into positive and negative sentiments which intern give rises to a problem of classifying such emotions into fear, joy, sad,surprise,compact etc. By separating client assessment for basic leadership and business analysis slant research is one of quickly developing and dependable device in this article.The main problem was to perform the sentimental analysis on the data collected from the events for detect the emotions of peoples. The KSSA is the new technique or methodology that has been adopted in this research paper to perform the sentimental analysis and we have achieved the best result as we have performed on huge number of data and achieved this much of result
Keyword: Emotion Detection, AS Approach, Business Analysis, Technical Events.
Scope of the Article: Predictive Analysis