An overview of investor sentiment: Identifying themes, trends, and future direction through bibliometric analysis

Kamath, Aditi N.; Shenoy, Sandeep S; N., Subrahmanya Kumar

doi:10.21511/imfi.19(3).2022.19

Cited by 10 publications

(4 citation statements)

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“…Additionally, by considering other bibliometric studies focusing on sentiment analysis in various areas, the remarkable contributions of both the USA and China have been observed, which in general, held the first positions. The reader can refer to the works of Kamath et al [51] in the area of investor sentiment, Kale [52] in the bibliometric analysis conducted on sentiment analysis in library and information science, and Yaqub et al [53] in the tourism industry, who highlight the top position occupied by the USA and the second position held by China, or to the works of Qiang et al [54] in the area of network public opinion and Nyakurukwa and Seetharam [55] regarding the evolution of social media sentiment in the stock market-who highlight the leader position of China, followed by the USA.…”

Section: Authorsmentioning

confidence: 99%

Sentiment Analysis in the Age of COVID-19: A Bibliometric Perspective

Sandu,

Cotfas,

Delcea

et al. 2023

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The global impact of the COVID-19 pandemic has been profound, placing significant challenges upon healthcare systems and the world economy. The pervasive presence of illness, uncertainty, and fear has markedly diminished overall life satisfaction. Consequently, sentiment analysis has gained substantial traction among scholars seeking to unravel the emotional and attitudinal dimensions of this crisis. This research endeavors to provide a bibliometric perspective, shedding light on the principal contributors to this emerging field. It seeks to spotlight the academic institutions associated with this research domain, along with identifying the most influential publications in terms of both paper volume and h-index metrics. To this end, we have meticulously curated a dataset comprising 646 papers sourced from the ISI Web of Science database, all centering on the theme of sentiment analysis during the COVID-19 pandemic. Our findings underscore a burgeoning interest exhibited by the academic community in this particular domain, evident in an astonishing annual growth rate of 153.49%. Furthermore, our analysis elucidates key keywords and collaborative networks within the authorship, offering valuable insights into the global proliferation of this thematic pursuit. In addition to this, our analysis encompasses an n-gram investigation across keywords, abstracts, titles, and keyword plus, complemented by an examination of the most frequently cited works. The results gleaned from these endeavors offer crucial perspectives, contribute to the identification of pertinent issues, and provide guidance for informed decision-making.

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Section: Authorsmentioning

confidence: 99%

Sentiment Analysis in the Age of COVID-19: A Bibliometric Perspective

Sandu,

Cotfas,

Delcea

et al. 2023

Information

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“…By analyzing other bibliometric papers, it has been observed that the abovementioned countries are also listed among the top contributors for the social media research in the age of COVID-19 [112], COVID-19 vaccination misinformation [40], health-related misinformation in social media [39], and sentiment analysis in times of COVID-19 [115]. Furthermore, it has been observed that both the USA and China have assumed top positions (either first or second position) regarding the contribution to the various fields such as investors sentiments [119], network public opinion [120], sentiment analysis in library and information science [121], social media sentiment in the stock market [122], and the tourism industry [123].…”

Section: Discussionmentioning

confidence: 99%

Mapping the Landscape of Misinformation Detection: A Bibliometric Approach

Sandu,

Ioanăș,

Delcea

et al. 2024

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The proliferation of misinformation presents a significant challenge in today’s information landscape, impacting various aspects of society. While misinformation is often confused with terms like disinformation and fake news, it is crucial to distinguish that misinformation involves, in mostcases, inaccurate information without the intent to cause harm. In some instances, individuals unwittingly share misinformation, driven by a desire to assist others without thorough research. However, there are also situations where misinformation involves negligence, or even intentional manipulation, with the aim of shaping the opinions and decisions of the target audience. Another key factor contributing to misinformation is its alignment with individual beliefs and emotions. This alignment magnifies the impact and influence of misinformation, as people tend to seek information that reinforces their existing beliefs. As a starting point, some 56 papers containing ‘misinformation detection’ in the title, abstract, or keywords, marked as “articles”, written in English, published between 2016 and 2022, were extracted from the Web of Science platform and further analyzed using Biblioshiny. This bibliometric study aims to offer a comprehensive perspective on the field of misinformation detection by examining its evolution and identifying emerging trends, influential authors, collaborative networks, highly cited articles, key terms, institutional affiliations, themes, and other relevant factors. Additionally, the study reviews the most cited papers and provides an overview of all selected papers in the dataset, shedding light on methods employed to counter misinformation and the primary research areas where misinformation detection has been explored, including sources such as online social networks, communities, and news platforms. Recent events related to health issues stemming from the COVID-19 pandemic have heightened interest within the research community regarding misinformation detection, a statistic which is also supported by the fact that half of the papers included in top 10 papers based on number of citations have addressed this subject. The insights derived from this analysis contribute valuable knowledge to address the issue, enhancing our understanding of the field’s dynamics and aiding in the development of effective strategies to detect and mitigate the impact of misinformation. The results spotlight that IEEE Access occupies the first position in the current analysis based on the number of published papers, the King Saud University is listed as the top contributor for the misinformation detection, while in terms of countries, the top-5 list based on the highest contribution to this area is made by the USA, India, China, Spain, and the UK. Moreover, the study supports the promotion of verified and reliable sources of data, fostering a more informed and trustworthy information environment.

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“…Academic background in this field is mixed. It is proved by bibliometric research on the stock market indices by Kamath et al (2022) and Zulfikar (2022).…”

Section: Literature Reviewmentioning

confidence: 94%

ESG vs conventional indices: Comparing efficiency in the Ukrainian stock market

Plastun

Makarenko

Huliaieva

et al. 2023

Investment Management and Financial Innovations

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This paper explores market efficiency in the Ukrainian stock market to determine whether there are differences between traditional and ESG indices. Different data properties related to market efficiency are explored: persistence (R/S analysis is used for these purposes), stationarity (ADF tests), normality (Kolmogorov-Smirnoff, Anderson-Darling test, etc.), resistance to market anomalies (Day of the week effect, abnormal returns and patterns they generate are tested using parametrical and non-parametrical statistical tests), etc. Database includes daily data from 2 conventional Ukrainian stock market indices (UX and PFTS) and ESG index (WIG Ukraine) over the period 2015–2022. The following hypothesis is tested in this paper: ESG indices are more efficient than traditional ones. The findings suggest that there are no significant differences between traditional and ESG indices: they have the same persistence, stationarity, do not fit normal distribution and are not influenced by explored market anomalies. So, despite the fact that companies listed in the ESG index are more transparent and thus characterized by lower information asymmetry, they are more liquid and popular among investors, ESG index is not more efficient than traditional ones. This might be the result of unfair practices called “washing” aimed at signaling the active ESG involvement with actual absence of it. This means that many ESG companies are actually traditional. To prevent such practices, the ESG reporting regulation needs to be revised. AcknowledgmentAlex Plastun gratefully acknowledges financial support from the Ministry of Education and Science of Ukraine (0121U100473).

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An overview of investor sentiment: Identifying themes, trends, and future direction through bibliometric analysis

Cited by 10 publications

References 50 publications

Sentiment Analysis in the Age of COVID-19: A Bibliometric Perspective

Sentiment Analysis in the Age of COVID-19: A Bibliometric Perspective

Mapping the Landscape of Misinformation Detection: A Bibliometric Approach

ESG vs conventional indices: Comparing efficiency in the Ukrainian stock market

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