Decision making using machine learning based opinion prediction model for smart governance

被引:0
|
作者
Kumar A. [1 ]
Sharma A. [1 ]
机构
[1] Department of Computer Science & Engineering, Delhi Technological University, Delhi
关键词
Big data; Decision making; Opinion mining; Policy evaluation; Scheme; Twitter;
D O I
10.2174/2213275912666191026123414
中图分类号
学科分类号
摘要
Background: Decision making requires a rigorous process of evaluation, which is an ana-lytical and organized process to figure out the present positive influences, favourable future pro-spects, existing shortcomings and ulterior complexities of any plan, program, practice or a polity. Evaluation of policy is an essential and vital process required to measure the performance or pro-gression of the scheme. The main purpose of policy evaluation is to empower various stakeholders and enhance their socio-economic environment. A large number of policies or schemes in different areas are launched/constituted by government in view of the citizen welfare. Although, the governmental policies intend to better shape up the quality of life of people but may also impact their eve-ryday's life. Objective: The contemplation of public opinion plays a very significant role in the process of policy evaluation. Therefore, the aim of this paper is to incorporate the concept of opinion mining in policy evaluation. An attempt has been made to elevate the process of policy evaluation by analyzing public opinion. Methods: A latest governmental scheme Saubhagya launched by the Indian government in 2017 has been selected for evaluation by applying supervised learning based opinion mining techniques. The data set of public opinion associated with this scheme has been captured by Twitter. Results: The result validates that the proposed methodology supports the optimizing process of policy evaluation and provides a more accurate and actual status of policy's effect among Indian citizen. As a result, this would aid in identifying and implementing the preventive and corrective measures required to be taken for a successful policy. Conclusion: The proposed methodology will stabilize and strengthen the process of policy evaluation which target towards favourable and flourishing future prospects concerning the socio-economic status of a nation. The results are quite exciting and further extension of work will be performed in order to develop and design a patent framework in the area of social big data analytics. © 2021 Bentham Science Publishers.
引用
收藏
页码:1402 / 1411
页数:9
相关论文
共 50 条
  • [21] Smart Home Resource Management based on Multi-Agent System Modeling Combined with SVM Machine Learning for Prediction and Decision-Making
    Zaouali, Kalthoum
    Ammari, Mohamed Las Saad
    Tabka, Mhamed
    Choueib, Amine
    Bouallegue, Ridha
    ACHI 2018: THE ELEVENTH INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTER-HUMAN INTERACTIONS, 2018, : 120 - 127
  • [22] A machine learning-based weather prediction model and its application on smart irrigation
    Khalifeh, Ala' F.
    AlQammaz, Abdullah Y.
    Abualigah, Laith
    Khasawneh, Ahmad M.
    Darabkh, Khalid A.
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2022, 43 (02) : 1835 - 1842
  • [23] Hybrid Model of Machine Learning Refractory Data Prediction Based on IoT Smart Cities
    Li, Xuewei
    Huang, Kai
    Xu, Lei
    WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2022, 2022
  • [24] A Machine Learning Model for Air Quality Prediction for Smart Cities
    Mahalingam, Usha
    Elangovan, Kirthiga
    Dobhal, Himanshu
    Valliappa, Chocko
    Shrestha, Sindhu
    Kedam, Giriprasad
    2019 INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, SIGNAL PROCESSING AND NETWORKING (WISPNET 2019): ADVANCING WIRELESS AND MOBILE COMMUNICATIONS TECHNOLOGIES FOR 2020 INFORMATION SOCIETY, 2019, : 452 - 457
  • [25] Deep learning and machine learning based air pollution prediction model for smart environment design planning
    Karthikeyan, B.
    Mohanasundaram, R.
    Suresh, P.
    Babu, J. Jagan
    GLOBAL NEST JOURNAL, 2023, 25 (05): : 11 - 19
  • [26] Public opinion prediction on social media by using machine learning methods
    Zhang, An-Jun
    Ding, Ru-Xi
    Pedrycz, Witold
    Chang, Zhonghao
    EXPERT SYSTEMS WITH APPLICATIONS, 2025, 269
  • [27] Political Opinion Mining for Popularity Prediction using Machine Learning Techniques
    Dharani Devi, G.
    Hemalatha, R.
    Pradeep, R.
    Jagan, G.
    2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering, RMKMATE 2023, 2023,
  • [28] Clinical Decision Making Using Machine Learning and ICU Data
    Tembhurne, Saurabh P.
    Neware, Shubhangi
    HELIX, 2018, 8 (05): : 4082 - 4087
  • [29] Machine Learning Based Decision-Making: A Sensemaking Perspective
    Li, Jingqi
    Namvar, Morteza
    Im, Ghiyoung P.
    Akhlaghpour, Saeed
    AUSTRALASIAN JOURNAL OF INFORMATION SYSTEMS, 2024, 28 : 1 - 22
  • [30] Machine Learning Based Bug Prediction Engine For Smart Contracts
    Gul, Ahmet
    Koroglu, Yavuz
    Sen, Alper
    2020 TURKISH NATIONAL SOFTWARE ENGINEERING SYMPOSIUM (UYMS), 2020, : 63 - 68