ANALYSIS OF STUDENT FEEDBACK ON FACULTY TEACHING USING SENTIMENT ANALYSIS AND NLP TECHNIQUES A Project report submitted in partial fulfilment of the requirements for the award of the degree of BACHELOR OF TECHNOLOGY IN COMPUTER SCIENCE AND ENGINEERING Submitted by M.RAVI VARMA 316126510160 R.VENKATESH 316126510172 S.V.PAVAN 316126510176 P.SAI TEJA 316126510183 Under the guidance of S. JOSHUA JOHNSON ASSISTANT PROFESSOR DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING ANIL NEERUKONDA INSTITUTE OF TECHNOLOGY AND SCIENCES (UGC AUTONOMOUS) (Permanently Affiliated to AU, Approved by AICTE and Accredited by NBA & NAAC with ‘A’ Grade) Sangivalasa, bheemili mandal, Visakhapatnam dist. (A.P) 2019-2020 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING ANIL NEERUKONDA INSTITUTE OF TECHNOLOGY AND SCIENCES (UGC AUTONOMOUS) (Affiliated to AU, Approved by AICTE and Accredited by NBA & NAAC with ‘A’ Grade) Sangivalasa, bheemili mandal, visakhapatnam dist. (A.P) BONAFIDE CERTIFICATE This is to certify that the project report entitled “ANALYSIS OF STUDENT FEEDBACK ON FACULTY TEACHING USING SENTIMENT ANALYSIS AND NLP TECHNIUQES” submitted by M.Ravi Varma (316126510160), R.Venkatesh (316126510172), S.V.Pavan (316126510176), P.Sai Teja (316126510183) in partial fulfillment of the requirements for the award of the degree of Bachelor of Technology in Computer Science and Engineering of Anil Neerukonda Institute of technology and sciences (A), Visakhapatnam is a record of bonafide work carried out under my guidance and supervision. SIGNATURE SIGNATURE DR.R.SIVARANJINI S.JOSHUA JOHNSON HEAD OF THE DEPARTMENT ASSISTANT PROFESSOR COMPUTER SCIENCE ENGINEERING COMPUTER SCIENCE ENGINEERING ANIL NEERUKONDA INSTITUTE OF ANIL NEERUKONDA INSTITUTE OF TECHNOLOGY&SCIENCES TECHNOLOGY&SCIENCES (AUTONOMOUS) (AUTONOMOUS) DECLARATION This is to certify that the project work entitled “Analysis of Student Feedback on Faculty Teaching Using Sentiment Analysis and NLP Techniques” is a bonafide work carried out by M.Ravi Varma, R.Venkatesh, S.V.Pavan, P.Sai Teja as a part of B.TECH final year 2nd semester of Computer science & engineering of ANITS, Visakhapatnam during the year 2016-2020. We, M.Ravi Varma, R.Venkatesh, S.V.Pavan, P.Sai Teja of final semester B.TECH ,in the department of Computer Science Engineering from ANITS, Visakhapatnam, hereby declare that the project work entitled “Analysis of Student Feedback on Faculty Teaching Using Sentiment Analysis and NLP Techniques” is carried out by us and submitted in partial fulfilment of the requirements for the award of Bachelor of Technology in Computer Science & Engineering , under Anil Neerukonda Institute Of Technology & Sciences during the academic year 2016-2020 and has not been submitted to any other university for the award of any kind of degree. M RAVI VARMA 316126510160 R VENKATESH 316126510172 S V PAVAN 316126510176 P SAI TEJA 316126510183 ACKNOWLEDGEMENT An endeavor over a long period can be advice and support of many well-wishers. We take this opportunity to express our gratitude and appreciation to all of them. We owe our tributes to Dr.R.Sivaranjani, Head of the Department, Computer Science & Engineering for her valuable support and guidance during the period of project implementation. We wish to express our sincere thanks and gratitude to our project guide S.Joshua Johnson, Assistant Professor, Department of Computer Science And Engineering, ANITS for their simulating discussions, in analyzing problems associated with our project work and for guiding us throughout the project. Project meeting were highly informative. We express our sincere thanks for the encouragement, untiring guidance and the confidence they had shown in us. We are immensely indebted for their valuable guidance throughout our project. We also thank our B.Tech project coordinator B.Mahesh, for his support and encouragement. We also thank all the staff members of Computer Science & Engineering department for their valuable advice. We also thank Principal and supporting staff for providing resources as and when required. M.Ravi Varma 316126510160 R.Venkatesh 316126510172 S.V.Pavan 316126510176 P.Sai Teja 316126510183 ABSTRACT In education system, student’s feedback is important to measure the quality of teaching. Students’ feedback can be analyzed using lexicon-based approach to identify the student’s positive or negative attitude. The main objective of this research is to analysis the Students feedback and obtains the opinion. In most of the existing teaching evaluation system, the intensifier words and blind negation words are not considered. The level of opinion result isn’t displayed-whether positive or negative opinion. To address this problem, we propose to analyze the student’s text feedback automatically using lexicon based approach to predict the level of teaching performance. The opinion result is represented as whether strongly positive, moderately positive, weakly positive, strongly negative, moderately negative, weakly negative or neutral. Key words: Opinion mining, Sentiment Analysis, Teaching Evaluation, Lexicon based approach, corpus based approach, Dictionary based approach, Qualitative information, quantitative information, Afinn lexicon. CONTENTS ABSTRACT Vi LIST OF FIGURES viii LIST OF TABLES ix LIST OF ABBREVATIONS x CHAPTER 1 INTRODUCTION 1 1.1 Supervised methods 2 1.2 Unsupervised methods 3 1.3 Semi Supervised methods 6 1.4 Problem Statement 7 CHAPTER 2 LITERATURE SURVEY 2.1 Introduction 8 2.2 Existing methods for research papers 8 CHAPTER 3 SENTIMENT ANALYSIS PROCESS 3.1 Lexicon based approach 12 3.1.1 Dictionary based approach 13 3.1.2 Corpus based approach 14 3.2 Machine Learning based approach 15 3.3 Hybrid approach 16 CHAPTER 4 METHODOLOGY 4.1 Proposed System 17 4.2 Analyzing sentiment in student feedback 19 4.2.1 Liu Lexicon 20 4.2.2 Afinn Lexicon 20 4.3 System Architecture 22 4.3.1 Preprocessing 23 4.3.2 Opinion words identification 23 4.3.3 Assign polarity values 24 4.3.4 Total sentiment score 24 4.3.5 Calculate average polarity value 25 CHAPTER 5 MODULES DIVISION & UML DIAGRAMS 5.1 Modules 26 5.1.1 Student module 26 5.1.2 Faculty Module 26 5.1.3 Admin Module 26 5.2 Uml Diagrams 27 5.2.1 Use case diagrams 27 5.2.2 Class diagram 31 5.2.3 Activity diagrams 33 CHAPTER 6 SYSTEM REQUIREMENTS 6.1 Software Requirements 37 6.2 Hardware Requirement 38 6.3 XAMPP Software 38 6.4 ANACONDA Software 39 CHAPTER 7 RESULTS AND DISCUSSIONS 41 7.1 Student Login 43 7.2 Student Feedback 44 7.3 Admin Portal 45 7.4 Faculty Portal 50 7.5 Sample Input 52 7.6 Graphical Output 53 7.6 Sample Code 54 CHAPTER 8 CONCLUSION AND FUTURE SCOPE 71 REFERENCES 72 LIST OF FIGURES Figure Number Name of the Figure Page number 4.1 Block diagram of proposed system 18 4.2 Lexicon based sentiment approach 21 4.3 System Architecture 22 5.2.1.1 Use case Diagram of Student login 29 5.2.1.2 Use case Diagram of Faculty login 30 5.2.2 Class Diagram 32 5.2.3.1 Activity Diagram of Admin 34 5.2.3.2 Activity Diagram of Faculty 35 5.2.3.3 Activity Diagram of Student 36 7.1 Login Form 43 7.2.1 Student Feedback Form 44 7.2.2 Student Feedback Form 1 45 7.3.1 Admin Portal 46 7.3.2 Instructions to Uploading the Excel 47 7.3.3 Uploading the Excel File 48 7.3.4 Faculty Data to Enter 49 7.4.1 Faculty Home Page 50 7.4.2 Selection of View Result’s 51 7.6 Graphical Representation of Feedback 63 LIST OF TABLES Table Number Table Name Page Number 4.3.5 Opinion Word Analyzer 25 7.5 Student Feedback 52 LIST OF ABBREVIATIONS ESM : Explanation and Subject Command VBL : Voice and Body Language DCL : Doubt Clearance and Interaction ISC : In time syllabus Coverage CHAPTER-1: INTRODUCTION Sentimental analysis is a method for identifying the sentiment expressed in texts. The need of Sentiment Analysis of text has gained more importance in today’s situations faced by the people of the world. Generally, there are three approaches in sentimental analysis. They are lexicon based, machine learning and hybrid approach. In machine learning technique, it uses unsupervised learning or supervised learning. Classification problem can be carried out using several algorithms like support vector machine, naive bayes, random forest. In lexicon based method sentiment polarity of the textual content is detected using sentiment lexicon. A lexicon is a list of words with associated sentiment polarity Sentiment analysis is a process for tracking the mood of the people about any particular topic by review. In general, opinion may be the result of people’s personal feelings, beliefs, sentiments and desires etc. This research work focus on students comments Analyzing students comments using sentiment analysis approaches can classify the students positive or negative feelings. Student’s feedback can highlight various issues students may have with a lecture. Sometimes students do not understand what the lecturer is trying to explain, thus by providing feedbacks, students can indicate this to the lecturer. The Input we take is qualitative data rather than quantitative data. The processing of qualitative data analysis is very important and it can enhance the teacher evaluation effectiveness. Evaluating performance of faculty members is becoming an essential component of an education management system. It not only helps in improving the course contents and quality but is also often used during the annual appraisal process of faculty members. The evaluation is typically collected at the end of each course on a set of question which are answered. The evaluation form, however, also provides room for open feedback which typically is not included in the performance evaluation/appraisal due to lack of automated text analytics methods. The textual data may contain useful insight about subject knowledge of the teacher, regularity, and presentation skills and may also provide suggestions to improve the teaching of quality.