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Problems of Data Processing in the Problem of Modeling Advertising Campaigns in Social Networks Using Python Libraries. / Fursov, Dmitry ; Krylatov, Alexander ; Svirkin, Michael ; Prokhorenko, Filip .

Data Science and Algorithms in Systems: Proceedings of 6th Computational Methods in Systems and Software 2022. ред. / R. Silhavy; P. Silhavy; Z. Prokopova. Том 2 Springer Nature, 2023. стр. 990-1001 (LNNS; Том 597).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › Рецензирование

Harvard

Fursov, D, Krylatov, A, Svirkin, M & Prokhorenko, F 2023, Problems of Data Processing in the Problem of Modeling Advertising Campaigns in Social Networks Using Python Libraries. в R Silhavy, P Silhavy & Z Prokopova (ред.), Data Science and Algorithms in Systems: Proceedings of 6th Computational Methods in Systems and Software 2022. Том. 2, LNNS, Том. 597, Springer Nature, стр. 990-1001, 6th Computational Methods in Systems and Software 2022, Прага, Чехия, 13/10/22. https://doi.org/10.1007/978-3-031-21438-7_85

APA

Fursov, D., Krylatov, A., Svirkin, M., & Prokhorenko, F. (2023). Problems of Data Processing in the Problem of Modeling Advertising Campaigns in Social Networks Using Python Libraries. в R. Silhavy, P. Silhavy, & Z. Prokopova (Ред.), Data Science and Algorithms in Systems: Proceedings of 6th Computational Methods in Systems and Software 2022 (Том 2, стр. 990-1001). (LNNS; Том 597). Springer Nature. https://doi.org/10.1007/978-3-031-21438-7_85

Vancouver

Fursov D, Krylatov A, Svirkin M, Prokhorenko F. Problems of Data Processing in the Problem of Modeling Advertising Campaigns in Social Networks Using Python Libraries. в Silhavy R, Silhavy P, Prokopova Z, Редакторы, Data Science and Algorithms in Systems: Proceedings of 6th Computational Methods in Systems and Software 2022. Том 2. Springer Nature. 2023. стр. 990-1001. (LNNS). https://doi.org/10.1007/978-3-031-21438-7_85

Author

Fursov, Dmitry ; Krylatov, Alexander ; Svirkin, Michael ; Prokhorenko, Filip . / Problems of Data Processing in the Problem of Modeling Advertising Campaigns in Social Networks Using Python Libraries. Data Science and Algorithms in Systems: Proceedings of 6th Computational Methods in Systems and Software 2022. Редактор / R. Silhavy ; P. Silhavy ; Z. Prokopova. Том 2 Springer Nature, 2023. стр. 990-1001 (LNNS).

BibTeX

@inproceedings{0e2839526068494c92d86c32b4de4663,
title = "Problems of Data Processing in the Problem of Modeling Advertising Campaigns in Social Networks Using Python Libraries",
abstract = "The aim of the work is to create matrix of feature objects for machine learning problems. The task is to search for data sources, develop a preprocessing algorithm, process statistical community data and form a matrix of feature objects for its further use in the clustering problem. Methods used: data analysis, finding descriptive statistics, methods of Python libraries: Pandas, NumPy. The novelty of this study lies in solving the problem of searching for relevant data of social network communities and developing an algorithm that forms a matrix of feature objects for its further use by researchers. Result: the analysis of services providing statistics of social networks was carried out, a program code was developed that implements the algorithm for generating a matrix of feature objects. The practical significance lies in the processing relevant statistical data and using a matrix of feature objects in machine learning problems.",
keywords = "Matplotlib, NumPy, Pandas, Social media marketing, internet marketing, Machine learning, statistical modeling, Mathematical modeling, Data processing",
author = "Dmitry Fursov and Alexander Krylatov and Michael Svirkin and Filip Prokhorenko",
note = "Fursov, D., Krylatov, A., Svirkin, M., Prokhorenko, F. (2023). Problems of Data Processing in the Problem of Modeling Advertising Campaigns in Social Networks Using Python Libraries. In: Silhavy, R., Silhavy, P., Prokopova, Z. (eds) Data Science and Algorithms in Systems. CoMeSySo 2022. Lecture Notes in Networks and Systems, vol 597. Springer, Cham. https://doi.org/10.1007/978-3-031-21438-7_85; 6th Computational Methods in Systems and Software 2022, CoMeSySo2022 ; Conference date: 13-10-2022 Through 15-10-2022",
year = "2023",
doi = "10.1007/978-3-031-21438-7_85",
language = "English",
isbn = "9783031214370",
volume = "2",
series = "LNNS",
publisher = "Springer Nature",
pages = "990--1001",
editor = "R. Silhavy and P. Silhavy and Z. Prokopova",
booktitle = "Data Science and Algorithms in Systems",
address = "Germany",
url = "https://comesyso.openpublish.eu/",

}

RIS

TY - GEN

T1 - Problems of Data Processing in the Problem of Modeling Advertising Campaigns in Social Networks Using Python Libraries

AU - Fursov, Dmitry

AU - Krylatov, Alexander

AU - Svirkin, Michael

AU - Prokhorenko, Filip

N1 - Conference code: 6

PY - 2023

Y1 - 2023

N2 - The aim of the work is to create matrix of feature objects for machine learning problems. The task is to search for data sources, develop a preprocessing algorithm, process statistical community data and form a matrix of feature objects for its further use in the clustering problem. Methods used: data analysis, finding descriptive statistics, methods of Python libraries: Pandas, NumPy. The novelty of this study lies in solving the problem of searching for relevant data of social network communities and developing an algorithm that forms a matrix of feature objects for its further use by researchers. Result: the analysis of services providing statistics of social networks was carried out, a program code was developed that implements the algorithm for generating a matrix of feature objects. The practical significance lies in the processing relevant statistical data and using a matrix of feature objects in machine learning problems.

AB - The aim of the work is to create matrix of feature objects for machine learning problems. The task is to search for data sources, develop a preprocessing algorithm, process statistical community data and form a matrix of feature objects for its further use in the clustering problem. Methods used: data analysis, finding descriptive statistics, methods of Python libraries: Pandas, NumPy. The novelty of this study lies in solving the problem of searching for relevant data of social network communities and developing an algorithm that forms a matrix of feature objects for its further use by researchers. Result: the analysis of services providing statistics of social networks was carried out, a program code was developed that implements the algorithm for generating a matrix of feature objects. The practical significance lies in the processing relevant statistical data and using a matrix of feature objects in machine learning problems.

KW - Matplotlib

KW - NumPy

KW - Pandas

KW - Social media marketing

KW - internet marketing

KW - Machine learning

KW - statistical modeling

KW - Mathematical modeling

KW - Data processing

UR - https://www.mendeley.com/catalogue/71d22395-8b9f-3138-b8a8-5b126eb3b2f7/

U2 - 10.1007/978-3-031-21438-7_85

DO - 10.1007/978-3-031-21438-7_85

M3 - Conference contribution

SN - 9783031214370

VL - 2

T3 - LNNS

SP - 990

EP - 1001

BT - Data Science and Algorithms in Systems

A2 - Silhavy, R.

A2 - Silhavy, P.

A2 - Prokopova, Z.

PB - Springer Nature

T2 - 6th Computational Methods in Systems and Software 2022

Y2 - 13 October 2022 through 15 October 2022

ER -

ID: 103176560