Human Behavior Analysis Using Intelligent Big Data Analytics

Frontiers in Psychology

article

Muhammad Usman Tariq¹  Muhammad Babar²  Marc Poulin¹  Akmal Saeed Khattak³  Mohammad Dahman Alshehri⁴  Sarah Kaleem⁵ 

[1] Abu Dhabi School of Management, United Arab Emirates;Department of Computer Science, Allama Iqbal Open University;Department of Computer Science, Quaid-i-Azam University;College of Computers and Information Technology, Taif University;Department of Computing and Technology, Iqra University

关键词: human behavior;    big data;    artificial intelligence;    Apache Spark;    analytics;   

DOI  :  10.3389/fpsyg.2021.686610

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

Intelligent big data analysis is an evolving pattern in the age of big data science and artificial intelligence (AI). Analysis of organized data has been very successful, but analyzing human behavior using social media data becomes challenging. The social media data comprises a vast and unstructured format of data sources that can include likes, comments, tweets, shares, and views. Data analytics of social media data became a challenging task for companies, such as Dailymotion, that have billions of daily users and vast numbers of comments, likes, and views. Social media data is created in a significant amount and at a tremendous pace. There is a very high volume to store, sort, process, and carefully study the data for making possible decisions. This article proposes an architecture using a big data analytics mechanism to efficiently and logically process the huge social media datasets. The proposed architecture is composed of three layers. The main objective of the project is to demonstrate Apache Spark parallel processing and distributed framework technologies with other storage and processing mechanisms. The social media data generated from Dailymotion is used in this article to demonstrate the benefits of this architecture. The project utilized the application programming interface (API) of Dailymotion, allowing it to incorporate functions suitable to fetch and view information. The API key is generated to fetch information of public channel data in the form of text files. Hive storage machinist is utilized with Apache Spark for efficient data processing. The effectiveness of the proposed architecture is also highlighted.

【 授权许可】

CC BY