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The paper offers a survey of major Italian accounting scholars and their work for the period from 1900 to 1950. Apart from the late works of Rossi and Besta, the main focus is on the contributions by Zappa, who undoubtedly dominated the scene. In this period, as well as later, most Italian accountants and “aziendalisti” adopted the so‐called “income system”. Although its premises originated with Fabio Besta, master of the so‐called “patrimonial or proprietorship system”, the Italian School under Zappa gave this system a new theoretical basis that differed fundamentally from that of Besta. Zappa also developed the dynamic aspect of accounting and business economics that still prevails in Italy. The paper also devotes attention to other Italian scholars, less well‐known abroad. In the area of cost accounting it concentrates on the views of De Minico and his disciple Amodeo, but also mentions other contributors. The final Section deals with Italian contributions to accounting history during this period

The purpose of this paper is to offer a concise survey and comparison of Italian accounting research and academic publications during the second half of the 20th century.

The paper discusses the special relation between economia aziendale (business and public economics) and ragioneria (accounting) in Italy. The subsequent discussion on “financial accounting” includes a sub‐section on income‐orientation (vs capital‐orientation), especially important in Italy during this period, and the present crisis of economia aziendale as affecting ragioneria, contributions by major Italian accountants of the period (above all, Onida and Amaduzzi) are discussed. After a section on “cost and managerial accounting” (of less significance in Italy than financial accounting), and a look at “novel accounting trends”, the paper closes with a discussion of some representative historical studies of the period.

The paper reveals the changing international position of Italian accounting research.

The paper is limited by selecting the most prominent and relevant contributions among a host of pertinent publications.

In contrast to previous research, the paper offers an integrated survey of major Italian accounting publications of the entire second half of the 20th century.

The rapid advancement of technology in online communication and fingertip access to the Internet has resulted in the expedited dissemination of fake news to engage a global audience at a low cost by news channels, freelance reporters and websites. Amid the coronavirus disease 2019 (COVID-19) pandemic, individuals are inflicted with these false and potentially harmful claims and stories, which may harm the vaccination process. Psychological studies reveal that the human ability to detect deception is only slightly better than chance; therefore, there is a growing need for serious consideration for developing automated strategies to combat fake news that traverses these platforms at an alarming rate. This paper systematically reviews the existing fake news detection technologies by exploring various machine learning and deep learning techniques pre- and post-pandemic, which has never been done before to the best of the authors’ knowledge.

The detailed literature review on fake news detection is divided into three major parts. The authors searched papers no later than 2017 on fake news detection approaches on deep learning and machine learning. The papers were initially searched through the Google scholar platform, and they have been scrutinized for quality. The authors kept “Scopus” and “Web of Science” as quality indexing parameters. All research gaps and available databases, data pre-processing, feature extraction techniques and evaluation methods for current fake news detection technologies have been explored, illustrating them using tables, charts and trees.

The paper is dissected into two approaches, namely machine learning and deep learning, to present a better understanding and a clear objective. Next, the authors present a viewpoint on which approach is better and future research trends, issues and challenges for researchers, given the relevance and urgency of a detailed and thorough analysis of existing models. This paper also delves into fake new detection during COVID-19, and it can be inferred that research and modeling are shifting toward the use of ensemble approaches.

The study also identifies several novel automated web-based approaches used by researchers to assess the validity of pandemic news that have proven to be successful, although currently reported accuracy has not yet reached consistent levels in the real world.