Augmenting business statistics information by combining traditional data with textual data: a composite indicator approach

被引:0
|
作者
Camilla Salvatore
Silvia Biffignandi
Annamaria Bianchi
机构
[1] Utrecht University,Department of Methodology and Statistics
[2] Consultant in Economic Statistics Studies,Department of Economics
[3] University of Bergamo,undefined
来源
METRON | 2024年 / 82卷
关键词
Socio-economic indicators; Mazziotta–Pareto index; Sustainable development; Social media; Twitter;
D O I
暂无
中图分类号
学科分类号
摘要
Combining traditional and digital trace data is an emerging trend in statistics. In this respect, new data sources represent the basis for multi-purpose extraction of different statistical indicators, which contribute to augmenting the statistical information, for feeding smart statistics. The production of business statistics can benefit from the use of unstructured data, especially to study novel aspects which are not covered by traditional data sources. This paper proposes a methodological general framework for augmenting information by combining data, both structured and non structured. The statistical challenges of using unstructured data and their integration with traditional data are discussed. The methodological general framework is applied to the construction of smart composite indicators using social media data and their metadata. An empirical exercise illustrates how to apply the methodology in practice.
引用
收藏
页码:71 / 91
页数:20
相关论文
共 26 条
  • [21] A Multilingual Lexicon-based Approach for Sentiment Analysis in Social and Cultural Information System Data
    Jardim, Sandra
    Mora, Carlos
    Santana, Tiago
    PROCEEDINGS OF 2021 16TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI'2021), 2021,
  • [22] Integrated Multimedia City Data (iMCD): A composite survey and sensing approach to understanding urban living and mobility
    Thakuriah, Piyushimita
    Sila-Nowicka, Katarzyna
    Hong, Jinhyun
    Boididou, Christina
    Osborne, Michael
    Lido, Catherine
    McHugh, Andrew
    COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 2020, 80
  • [23] Emulating a virtual digital cohort study based on social media data as a complementary approach to traditional epidemiology: When, what for, and how?
    Fagherazzi, Guy
    Bour, Charline
    Ahne, Adrian
    DIABETES EPIDEMIOLOGY AND MANAGEMENT, 2022, 7
  • [24] A novel influence quantification model on Instagram using data science approach for targeted business advertising and better digital marketing outcomes
    Kumar, Sachin
    Saran, Kartikey
    Garg, Yashu
    Dubey, Gaurav
    Goel, Shivam
    Jha, Alok Nikhil
    Verma, Ajit Kumar
    SOCIAL NETWORK ANALYSIS AND MINING, 2024, 14 (01)
  • [25] Putting people in the picture: Combining big location-based social media data and remote sensing imagery for enhanced contextual urban information in Shanghai
    Jendryke, Michael
    Balz, Timo
    McClure, Stephen C.
    Liao, Mingsheng
    COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 2017, 62 : 99 - 112
  • [26] A Novel Mixed Methods Approach for Integrating Not-for-Profit Service Data via Qualitative Geographic Information System to Explore Authentic Experiences of Ill-Health: A Case Study of Rural Mental Health
    Kamstra, Peter
    Farmer, Jane
    McCosker, Anthony
    Gardiner, Fergus
    Dalton, Hazel
    Perkins, David
    Salvador-Carulla, Luis
    Bagheri, Nasser
    JOURNAL OF MIXED METHODS RESEARCH, 2023, 17 (04) : 419 - 442