Harnessing online stakeholder interactions for analyzing public inconvenience caused by construction of indian metro rail projects (Softcopy is also available) (Record no. 69579)
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| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
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| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | CEM TH-0401 |
| Item number | DAS |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Das, Srinjoy (PG190991) |
| 245 #0 - TITLE STATEMENT | |
| Title | Harnessing online stakeholder interactions for analyzing public inconvenience caused by construction of indian metro rail projects (Softcopy is also available) |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Date of publication, distribution, etc | 2021 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xix,143p. |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Formatted contents note | TABLE OF CONTENTS <br/>ABSTRACT i <br/>UNDERTAKING v <br/>CERTIFICATE vii <br/>ACKNOWLEDGEMENTS ix <br/>NOMENCLATURE xi <br/>LIST OF FIGURES xvii <br/>LIST OF TABLES xix <br/>1 CHAPTER-1: INTRODUCTION 3 <br/>1.1 Introduction 3 <br/>1.2 Objectives 4 <br/>1.3 Scope of the work 4 <br/>1.4 Methodology 4 <br/>2 CHAPTER-2: LITERATURE REVIEW 7 <br/>2.1 Overview 7 <br/>2.2 Public Inconvenience 7 <br/>2.3 Construction caused inconvenience 8 <br/>2.1 Public inconvenience caused by Metro Projects in India 13 <br/>2.2 Social Media as a database 16 <br/>2.3 Twitter as a preferred social medium for research 18 <br/>2.4 Advantages and Challenges of Social Media 19 <br/>2.5 Public participation using social media 20 <br/>2.6 Methodology 24 <br/>2.7 Metro Rail Agencies in India using social media platforms 24 <br/>2.8 Discussions and research position 25 <br/>3 CHAPTER-3: RESEARCH METHODOLOGY 27 <br/>3.1 Overview 27 <br/>3.2 Case Studies 27 <br/>3.3 Longitudinal Research and Sampling 28 <br/>3.4 Twitter Data 29 <br/>3.4.1 Data Extraction 30 <br/>3.4.2 Data Pre-processing 31 <br/>3.5 Content Analysis 32 <br/>3.6 Topic Modelling 32 <br/>3.7 Sentiment Analysis 33 <br/>3.8 Text Analytics 33 <br/>3.9 Social Network Analysis 34 <br/>4 CHAPTER-4: DATA COLLECTION 35 <br/>4.1 Overview 35 <br/>4.2 Developing Keywords for Sample 35 <br/>4.3 Extracting the data 37 <br/>4.4 Data De-duplication 38 <br/>4.5 Text Pre-processing 38 <br/>5 CHAPTER-5: DATA ANALYSIS AND RESULTS 41 <br/>5.1 Overview 41 <br/>5.2 Content Analysis of the Data 41 <br/>5.2.1 Usergroup Identification 41 <br/>5.3 Sentiment Analysis 42 <br/>5.4 Text Analytics and Topic Modeling 42 <br/>5.5 Social Network Analysis 43 <br/>5.6 Case Study 1 - Mumbai Metro 43 <br/>5.6.1 Inconvenience Categorization 43 <br/>5.6.2 User-groups Categorization 45 <br/>5.6.3 Sentiment Analysis 47 <br/>5.6.4 Text Analytics and Topic Modeling 50 <br/>5.6.5 Social Network Analysis 54 <br/>5.7 Case Study 2 – Pune Metro 57 <br/>5.7.1 Inconvenience Categorization 57 <br/>5.7.2 User-groups Categorization 59 <br/>5.7.3 Sentiment Analysis 61 <br/>5.7.4 Text Analytics and Topic Modeling 64 <br/>5.7.5 Social Network Analysis 68 <br/>5.8 Case Study 3- Bangalore Metro 72 <br/>5.8.1 Inconvenience Categorization 73 <br/>5.8.2 User-groups Categorization 75 <br/>5.8.3 Sentiment Analysis 77 <br/>5.8.4 Text Analytics and Topic Modeling 80 <br/>5.8.5 Social Network Analysis 83 <br/>5.9 Case Study 4 - Kolkata Metro 87 <br/>5.9.1 Inconvenience Categorization 87 <br/>5.9.2 User-groups Categorization 89 <br/>5.9.3 Sentiment Analysis 90 <br/>5.9.4 Text Analytics and Topic Modeling 94 <br/>5.9.5 Social Network Analysis 97 <br/>5.10 Semi-Structured Interviews 101 <br/>6 CHAPTER-6: CROSS – CASE ANALYSIS 105 <br/>6.1 Overview 105 <br/>6.2 Inconveniences Analysis Comparison 105 <br/>6.3 Sentiments Comparison 106 <br/>6.4 Stakeholders Comparison 107 <br/>6.5 Word Frequency Comparison 108 <br/>6.6 Social Network Analysis Comparison 110 <br/>7 CHAPTER-7: CONCLUSION AND RECOMMENDATION 115 <br/>7.1 Conclusion 115 <br/>7.2 Research Limitations 116 <br/>7.3 Future Scope 117 <br/>References 119 <br/>Annexure 1 – Inconvenience Parameters Comparison Table 125 <br/>Annexure 2 – Research Methodology of Twitter data across construction related papers 126 <br/>Annexure 3 – Research Methodology of Twitter data across non-construction related papers . 129 <br/>Annexure 4 – Different Research Methods applied on Twitter data across different papers ..... 132 <br/>Annexure 5 – Research Methodology 134 <br/>Annexure 6 – Semi-structured interview questions 135 <br/>Annexure 7 – Mumbai tweets examples 136 <br/>Annexure 8 – Pune tweets examples 138 <br/>Annexure 9 – Bangalore tweets examples 140 <br/>Annexure 10 – Kolkata tweets examples 142<br/> |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Devkar, Ganesh (Guide) |
| 890 ## - Country | |
| Country | India |
| 891 ## - Topic | |
| Topic | 2019 Batch |
| 891 ## - Topic | |
| Topic | Construction Engineering and Management |
| 891 ## - Topic | |
| Topic | FT-PG |
| Withdrawn status | Lost status | Damaged status | Not for loan | Collection code | Withdrawn status | Home library | Current library | Date acquired | Source of acquisition | Full call number | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Not For Loan | Faculty of Technology | CEPT Library | CEPT Library | 27/04/2022 | Faculty of Technology | CEM TH-0401 DAS | 023586 | 27/04/2022 | 27/04/2022 | Thesis |