Standard

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. ed. / R. Silhavy; P. Silhavy; Z. Prokopova. Vol. 2 Springer Nature, 2023. p. 990-1001 (LNNS; Vol. 597).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

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. in R Silhavy, P Silhavy & Z Prokopova (eds), Data Science and Algorithms in Systems: Proceedings of 6th Computational Methods in Systems and Software 2022. vol. 2, LNNS, vol. 597, Springer Nature, pp. 990-1001, 6th Computational Methods in Systems and Software 2022, Прага, Czech Republic, 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. In R. Silhavy, P. Silhavy, & Z. Prokopova (Eds.), Data Science and Algorithms in Systems: Proceedings of 6th Computational Methods in Systems and Software 2022 (Vol. 2, pp. 990-1001). (LNNS; Vol. 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. In Silhavy R, Silhavy P, Prokopova Z, editors, Data Science and Algorithms in Systems: Proceedings of 6th Computational Methods in Systems and Software 2022. Vol. 2. Springer Nature. 2023. p. 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. editor / R. Silhavy ; P. Silhavy ; Z. Prokopova. Vol. 2 Springer Nature, 2023. pp. 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