Sayantan Adak, Souvic Chakraborty, Paramtia Das, Mithun Das, A. Dash, Rima Hazra, Binny Mathew, Punyajoy Saha, Soumya Sarkar, Animesh Mukherjee
{"title":"Mining the online infosphere: A survey","authors":"Sayantan Adak, Souvic Chakraborty, Paramtia Das, Mithun Das, A. Dash, Rima Hazra, Binny Mathew, Punyajoy Saha, Soumya Sarkar, Animesh Mukherjee","doi":"10.1002/widm.1453","DOIUrl":null,"url":null,"abstract":"The evolution of Artificial Intelligence (AI)‐based systems and applications have pervaded everyday life to make decisions that have a momentous impact on individuals and society. With the staggering growth of online data, often termed as the online infosphere, it has become paramount to monitor the infosphere to ensure social good as AI‐based decisions are severely dependent. This survey aims to provide a comprehensive review of some of the most important research areas related to the infosphere, focusing on the technical challenges and potential solutions. The survey also outlines some of the important future directions. We begin by focussing on the collaborative systems that have emerged within the infosphere with a special thrust on Wikipedia. In the follow‐up, we demonstrate how the infosphere has been instrumental in the growth of scientific citations and collaborations, thus fuelling interdisciplinary research. Finally, we illustrate the issues related to the governance of the infosphere, such as the tackling of the (a) rising hateful and abusive behavior and (b) bias and discrimination in different online platforms and news reporting.","PeriodicalId":48970,"journal":{"name":"Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery","volume":"9 1","pages":""},"PeriodicalIF":6.4000,"publicationDate":"2021-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1002/widm.1453","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 1
Abstract
The evolution of Artificial Intelligence (AI)‐based systems and applications have pervaded everyday life to make decisions that have a momentous impact on individuals and society. With the staggering growth of online data, often termed as the online infosphere, it has become paramount to monitor the infosphere to ensure social good as AI‐based decisions are severely dependent. This survey aims to provide a comprehensive review of some of the most important research areas related to the infosphere, focusing on the technical challenges and potential solutions. The survey also outlines some of the important future directions. We begin by focussing on the collaborative systems that have emerged within the infosphere with a special thrust on Wikipedia. In the follow‐up, we demonstrate how the infosphere has been instrumental in the growth of scientific citations and collaborations, thus fuelling interdisciplinary research. Finally, we illustrate the issues related to the governance of the infosphere, such as the tackling of the (a) rising hateful and abusive behavior and (b) bias and discrimination in different online platforms and news reporting.
期刊介绍:
The goals of Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery (WIREs DMKD) are multifaceted. Firstly, the journal aims to provide a comprehensive overview of the current state of data mining and knowledge discovery by featuring ongoing reviews authored by leading researchers. Secondly, it seeks to highlight the interdisciplinary nature of the field by presenting articles from diverse perspectives, covering various application areas such as technology, business, healthcare, education, government, society, and culture. Thirdly, WIREs DMKD endeavors to keep pace with the rapid advancements in data mining and knowledge discovery through regular content updates. Lastly, the journal strives to promote active engagement in the field by presenting its accomplishments and challenges in an accessible manner to a broad audience. The content of WIREs DMKD is intended to benefit upper-level undergraduate and postgraduate students, teaching and research professors in academic programs, as well as scientists and research managers in industry.