Qualitative Sentiment Analysis with Implementation of Neuro-Linguistic Programming Techniques
Arun Kumar1, Supriya P. Panda2
1Arun Kumar*, Department of Computer Science and Engineering, Manav Rachna International Institute of Research and Studies, Faridabad India.
2Supriya P. Panda, Department of Computer Science and Engineering, Manav Rachna International Institute of Research and Studies, Faridabad, India.
Manuscript received on January 13, 2020. | Revised Manuscript received on January 22, 2020. | Manuscript published on February 10, 2020. | PP: 2556-2560 | Volume-9 Issue-4, February 2020. | Retrieval Number: D1937029420/2020©BEIESP | DOI: 10.35940/ijitee.D1937.029420
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© 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: This Paper lights on Neuro-Linguistic Programming (NLP) Techniques, which is used to implement with the help of Qualitative Sentiment surveys. Neuro-Linguistic Programming techniques with Qualitative Sentiment Surveys helps in determining the behavior pattern of the human mind. Nowadays there is a huge amount of data available related to many social aspects. Participants’ satisfaction is the key factor for Qualitative Surveys. In this paper, Neuro-Linguistic Programming techniques are used to change the behavior patterns of the human mind. Datasets of 81 participants are being used for analysis. NLP thinking, imagining and feeling techniques are used by the participants to make a change in their behavior pattern. Results are shown in tabular form. Participants’ satisfactory results are shown with the help of python by using data visualization and matplotlib.
Keywords: Neuro-Linguistic Programming (NLP), Qualitative Sentiment Analysis (QSA), NLP Tools and Techniques, Data Visualization
Scope of the Article: Advanced Computing Architectures and New Programming Models