Big data, computational social science, and other recent innovations in social network analysis

Tindall, David B.; McLevey, John; Koop-Monteiro, Yasmin; Graham, Alexander V.

doi:10.1111/cars.12377

Cited by 10 publications

(10 citation statements)

References 108 publications

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“…e scale of big data is so huge that it is impossible to directly obtain the desired information from it, and it needs to be processed and analyzed, collectively known as data mining [16]. Internet articles, social media text messages, and long and short videos are very important components of big data, and for the development of Marxist influence, the massive amount of Internet data that have accumulated over decades has considerable mining value [17]. To mine these data requires more knowledge about big data, which can be classified according to the distribution form of the data: structured big data, semi-structured big data, and unstructured big data.…”

Section: Introductionmentioning

confidence: 99%

The Basic Principles of Marxism with the Internet as a Carrier

Ruichen

2022

Mathematical Problems in Engineering

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We live in a real society today with the Internet as the carrier. Marxist philosophy is of great significance to the study of computer science and technology majors, such as the standardization of learning methods and the improvement of learning horizons. In order to study the ideology of the current Internet carrier, this study first introduces the ideology in the Internet scenario and again describes the basic principles of Marxism. Web text data were collected from both static and dynamic websites, and the data were initially preprocessed using the ICTCLAS word separation tool. After that, a text lexicon set related to Marxism was built and combined with the surplus value calculation formula. Analysis of the text data shows that the expectation error of the Internet population approximately obeys a positive-term distribution, and the online text data are feasible in the estimation of the influence of Marxism. The statistical results show that the percentage of serious philosophical discussions from 2017 to 2021 in which Marxism is mentioned has steadily increased from 62% to 78%, indicating that Marxism still has great influence to this day. For these three different attitudes toward Marxism, the number of comments agreeing and disagreeing differed significantly, indicating that different groups of people show very different attitudes toward Marxism.

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Section: Introductionmentioning

confidence: 99%

The Basic Principles of Marxism with the Internet as a Carrier

Ruichen

2022

Mathematical Problems in Engineering

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“…Social science research often involves collecting and analyzing vast amounts of data to answer complex research questions. Tindall et al (2022) highlight the role of big data and computational social science in social network analysis, particularly in data collection, statistical inference, and ethical considerations. Aravindh and Thirupathi (2019) compare the use of quantitative and qualitative research methods in social science, emphasizing the depth and scope of qualitative research.…”

Section: Introductionmentioning

confidence: 99%

My Data Are Ready, How Do I Analyze Them: Navigating Data Analysis in Social Science Research

Fodouop Kouam

2024

int.jour.sci.res.mana

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This paper offers a practical guide for researchers to effectively analyze their data in social science research, addressing the challenges and pitfalls commonly encountered in data analysis. By exploring various data analysis techniques, highlighting key challenges such as data quality issues and statistical assumptions violations, and providing practical tips and guidelines, this study fills a gap in the existing literature by offering a comprehensive approach to navigating data analysis in social science research. The significance of this study lies in its potential to improve the quality and reliability of research findings in the social sciences, equipping researchers with the necessary knowledge and skills to conduct robust data analysis. This study is a valuable resource for researchers seeking to enhance their analytical skills, avoid common pitfalls, and advance knowledge in their field of study.

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“…However, animation databases are becoming larger and larger, and college art students have to spend a lot of time and effort to find the right animation for them. In the past, Users were limited to searching using keywords such as name, director, and style of animation, and the variations among users were not considered in the search results, leading to biased results [14].…”

Section: Introductionmentioning

confidence: 99%

Animation Media Art Teaching Design Based on Big Data Fusion Technology

Wang,

Tao

2024

IJACSA

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Animation, as an ancient art expression form, still has vigorous development, and the need for animation talents in society is increasing daily. This study first introduces the definition of animation and the development of animation at home and abroad. After that, the classification regression tree algorithm's principle and function theorem are described. This study divides the data into original and new animations based on big data fusion technology. It establishes a media art teaching system with search, recommendation, and playback as the three cores. Additionally, iteration is used to calculate the optimal hidden semantic matrix, a comparison is made between the benefits and drawbacks of the Sigmoid, Tanh, and ReLU functions, and lastly, the activation function chosen is the ReLU function. Compared with the loss value in the ideal case, the experimental findings comply with the likely criteria, and the categorical regression tree algorithm model predicts an error rate that falls within acceptable limits. Practically speaking, it is known that when the hidden factor dimension is 12, the system model works best for characterizing animation features. The comparison shows that the non-standard collaborative filtering recommendation system is inferior to the recommendations filtered by the categorical regression tree algorithm model. Following the use of the system, the students' drawing and directing abilities, animation scope, and animation appreciation level all improved significantly. The questionnaire survey concluded that the teachers and students of animation majors in universities were satisfied with the system.

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Big data, computational social science, and other recent innovations in social network analysis

Cited by 10 publications

References 108 publications

The Basic Principles of Marxism with the Internet as a Carrier

The Basic Principles of Marxism with the Internet as a Carrier

My Data Are Ready, How Do I Analyze Them: Navigating Data Analysis in Social Science Research

Animation Media Art Teaching Design Based on Big Data Fusion Technology

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