piyush ghasiya | Jawaharlal Nehru University (original) (raw)

Papers by piyush ghasiya

Research Square (Research Square), Nov 29, 2022

The popularity of the instant messaging app Telegram in Ukraine and Russia was strong even before... more The popularity of the instant messaging app Telegram in Ukraine and Russia was strong even before the still-ongoing Russian invasion of Ukraine. However, since 24 February 2022 (when the Russian invasion began), it has seen huge increases in subscribers and even become the primary communication and news source in Ukraine. In this exploratory research, we analysed Telegram channels from both Ukraine (@UkraineNow-the official channel of the Ukrainian government, and @V_Zelen-skiy_official-the official channel of Ukraine's President Volodymyr Zelenskyy) and Russia (@rt_russian-the official channel of the news network RT) to discern the content of posts during this invasion. Our analysis of 37,172 posts in total showed that while @UkraineNow is particularly being used to communicate invasion-related news, @rt_russian is working as merely an extension of RT, which is part of the pro-Kremlin propaganda and disinformation ecosystem. However, Zelenskyy has opted for a completely different approach: he has used his Telegram channel to encourage Ukrainians and garner support from the World. The present conflict is at a critical juncture, and our timely research seeks to determine how both countries' governments are utilizing Telegram as a weapon for the information war and what impact this has on ground.

Frontiers in Fake Media Generation and Detection

Hindutva, the core political ideology of India's current ruling party, the Bharatiya Janata P... more Hindutva, the core political ideology of India's current ruling party, the Bharatiya Janata Party (BJP), seeks to transform constitutionally secular India into a Hindu Rashtra (`Hindu nation'). Although Hindutva has all of the features of right-wing extremism (RWE), it is nevertheless viewed as a sociopolitical phenomenon due to the Eurocentric nature of RWE discourse. Recent theoretical and analytical research has sought to showcase the similarity between RWE and Hindutva, whereas empirical research on their relationship has not been conducted. To fill that gap, in our study we collected 15 million tweets, and in network analysis, identified prominent themes of RWE, including exclusionary nationalism, conspiracy theories, and anti-minority violence and hate speech among the supporters of Hindutva and BJP. Furthermore, our toxicity analysis performed to understand which themes produced higher levels of toxicity, we found that Hindi-language tweets related to conspiracy theor...

The popularity of the instant messaging app Telegram in Ukraine and Russia was strong even before... more The popularity of the instant messaging app Telegram in Ukraine and Russia was strong even before the still-ongoing Russian invasion of Ukraine. However, since 24 February 2022 (when the Russian invasion began), it has seen huge increases in subscribers and even become the primary communication and news source in Ukraine. In this exploratory research, we analyzed Telegram channels from both Ukraine (@UkraineNow — the official channel of the Ukrainian government, and @V_Zelenskiy_official — the official channel of Volodymyr Zelenskyy) and Russia (@rt_russian — the official channel of the news network RT) to discern the content of posts during this invasion. Our analysis of 37,172 posts in total showed that while @UkraineNow is particularly being used to communicate invasion-related news, @rt_russian is working as merely an extension of RT, which is part of the pro-Kremlin propaganda and disinformation ecosystem. However, Zelenskyy has opted for a completely different approach: he has...

SSRN Electronic Journal, 2022

Despite the widespread global concerns on the potential detrimental effects of misinformation on ... more Despite the widespread global concerns on the potential detrimental effects of misinformation on democracy, the vast majority of studies still focus on Western countries. As a result, we disproportionately know more about wealthy countries characterized by lasting democratic traditions and pluralistic media systems than what we know about contexts where these institutions are yonder and more fragile. This work contributes to filling this gap by applying to the case of India an approach to map and study networks of coordinated social media accounts that spread problematic health-related content on Indian Facebook and Instagram.

During the initial months of the COVID-19 pandemic, the world saw lots of incidents of hate speec... more During the initial months of the COVID-19 pandemic, the world saw lots of incidents of hate speech, xenophobia, and discrimination where a specific community or people were targeted or accused of being spreaders of the Coronavirus disease. One such prominent episode happened in India, where the Muslim community was targeted for spreading COVID-19. This episode later became known as the “Tablighi Jamaat Controversy” (TJC). We analyzed Facebook posts by public groups during the five months (March to August 2020) that this furor raged to find the major actors and their link-sharing behavior and the presence of (if any) fake news and misinformation. We found that Islamophobic hate speech was spread by the Facebook groups that are Pro-BJP (Bhartiya Janta Party – the leading party in the present Indian government) and have a right-wing ideology, while other groups (anti-hate) were countering the hate. We also found that the hate spreaders were extremely active (three times faster) in shar...

During the initial months of the COVID-19 pandemic, the world saw lots of incidents of hate speec... more During the initial months of the COVID-19 pandemic, the world saw lots of incidents of hate speech, xenophobia, and discrimination where a specific community or people were targeted or accused of being spreaders of the Coronavirus disease. One such prominent episode happened in India, where the Muslim community was targeted for spreading COVID-19. This episode later became known as the “Tablighi Jamaat Controversy” (TJC). We analyzed Facebook posts by public groups during the five months (March to August 2020) that this furor raged to find the major actors and their link-sharing behavior and the presence of (if any) fake news and misinformation. We found that Islamophobic hate speech was spread by the Facebook groups that are Pro-BJP (Bhartiya Janta Party – the leading party in the present Indian government) and have a right-wing ideology, while other groups (anti-hate) were countering the hate. We also found that the hate spreaders were extremely active (three times faster) in shar...

International Journal of Semantic Computing

Cybersecurity is becoming indispensable for everyone and everything in the times of the Internet ... more Cybersecurity is becoming indispensable for everyone and everything in the times of the Internet of Things (IoT) revolution. Every aspect of human society — be it political, financial, technological, or cultural — is affected by cyber-attacks or incidents in one way or another. Newspapers are an excellent source that perfectly captures this web of cybersecurity. By implementing various NLP techniques such as tf-idf, word embedding and sentiment analysis (SA) (machine learning method), this research will examine the cybersecurity-related articles from 18 major newspapers (English language online version) from six countries (three newspapers from each country) collected within one year from April 2018 till March 2019. The first objective is to extract the crucial events from each country, which we will achieve by our first step — ‘information extraction.’ The next objective is to find out what kind of sentiments those crucial issues garnered, which we will accomplish from our second s...

CHI Conference on Human Factors in Computing Systems

Deepfakes are synthetic content generated using advanced deep learning and AI technologies. The a... more Deepfakes are synthetic content generated using advanced deep learning and AI technologies. The advancement of technology has created opportunities for anyone to create and share deepfakes Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

Digital Scholarship in the Humanities

For Japan—a country that has always been described with virtually no major natural resources such... more For Japan—a country that has always been described with virtually no major natural resources such as oil, gas, and coal—the Middle Eastern region has a special place in its economic and foreign policy. In 2017, 39% of Japan’s energy came from oil, and 87% of Japan’s imported oil came from the Middle East, predominantly Saudi Arabia and the UAE. The above facts are enough to discern the critical significance of the Middle Eastern region for Japan. For Japan to have an unhindered supply of oil and other natural resources, it is pertinent that this region remains peaceful. In this scenario, the Middle East-related articles in Japan’s newspapers can help understand Japan’s perspective towards the Middle East. This paper would first apply the topic modelling approach non-negative matrix factorization (NMF) on Middle East-related articles from three newspapers of Japan. After discovering crucial topics, we would utilize traditional supervised machine learning algorithms to determine the o...

ArXiv, 2021

Currently, the significance of social media in disseminating noteworthy information on topics suc... more Currently, the significance of social media in disseminating noteworthy information on topics such as health, politics, and the economy is indisputable. During the COVID-19 pandemic, anti-vaxxers use social media to distribute fake news and anxiety-provoking information about the vaccine, which may harm the public. Here, we characterize the psycho-linguistic features of anti-vaxxers on the online social network Twitter. For this, we collected COVID-19 related tweets from February 2020 to June 2021 to analyse vaccination stance, linguistic features, and social network characteristics. Our results demonstrated that, compared to pro-vaxxers, anti-vaxxers tend to have more negative emotions, narrative thinking, and worse moral tendencies. This study can advance our understanding of the online anti-vaccination movement, and become critical for social media management and policy action during and after the pandemic.

This dataset is consist news articles related to COVID-19 from UK, India, Japan and South Korea n... more This dataset is consist news articles related to COVID-19 from UK, India, Japan and South Korea newspapers.

Globalization has connected the nations of the world in a way never seen before. Happenings or ev... more Globalization has connected the nations of the world in a way never seen before. Happenings or events in one nation has the potential to impact other nations also. By collecting and analyzing cybersecurity-related articles from three major national newspapers of Japan, this research is trying to find out and understand Japan’s newspaper reporting on the cybersecurity issue. Content analysis of those cybersecurity-related articles is used to find critical themes and patterns. The content analysis found that the contention over 5G between the U.S. and China is the most critical issue in Japanese newspapers. From an international relations perspective, the issue between the U.S. and China over 5G is an adverse event represented in newspapers with words such as tussle, tech-war, and contention, but by performing sentiment analysis (content-based analysis) on the articles only related to Huawei, this research tried to find how machine categorize this issue. Then this research critically ...

Recent advancements in the field of Information Technology (IT) have not only changed the way peo... more Recent advancements in the field of Information Technology (IT) have not only changed the way people consume news but also made it possible for researchers to analyze a plethora of news, especially when the headlines are changing every minute. Big data, Natural Language Processing (NLP) and Machine Learning (ML) techniques are becoming staple for researchers of every domain to discover patterns and themes in the vast amount of data. This research would utilize NPL and ML techniques to analyze cybersecurity-related newspaper articles of major newspapers (digital version) from Japan and the US. Japan and the US are close allies, and they are collaborating in the field of cybersecurity owing to its rising significance for nations. However, as the demography, culture, and political behavior are different in both countries, it would be fascinating and very critical to analyze how newspapers from both countries are dealing with cybersecurity issues.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is wreaking havoc. This virus has in... more Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is wreaking havoc. This virus has infected more than 62.01 million and killed around 1.44 million people worldwide in less than a year. For the past 11 months, this is the most critical issue that the world is dealing with. Hence, there is a rapid accumulation of coronavirus-related news. Natural language processing (NLP) and machine learning (ML) methods such as topic modeling receive much attention because of their ability to discover hidden themes and issues from large unstructured text data. We collected 63,424 COVID-19/coronavirus themed news articles from Japanese and Indian English newspapers and applied the recently proposed Top2Vec model to analyze and extract major topics. Our research finds out that both countries’ media reported heavily about the problems that arise due to coronavirus in sports, education, and entertainment sectors. Our findings also point out that Indian media gave very little space to the iss...

2021 International Conference on Information Networking (ICOIN)

Machine Learning (ML) and specifically Natural Language Processing (NLP) are increasingly used as... more Machine Learning (ML) and specifically Natural Language Processing (NLP) are increasingly used as tools in the cybersecurity world. These NLP tools bring new capabilities that support both defenders and attackers in their activities, whether it is risk scenarios such as events and threats or security operations. Ours is a unique case study as we are investigating cybersecurity news on a national and global level. This large study covered six countries and 18 major newspapers and analyzed thousands of cybersecurity articles using the Nonnegative Matrix Factorization (NMF) topic modeling method. News making and policymaking complement each other in forming national identities. This research aims to provide the foundation for the field of Cybersecurity in this direction. Our results showed the US dominance and its significance for other countries. This research also highlighted that much of the US media’s cybersecurity reporting focuses on domestic issues, unlike other nations.

IEEE Access

Newspapers are very important for a society as they inform citizens about the events around them ... more Newspapers are very important for a society as they inform citizens about the events around them and how they can impact their life. Their importance becomes more crucial and indispensable in the times of health crisis such as the current COVID-19 pandemic. Since the starting of this pandemic newspapers are providing rich information to the public about various issues such as the discovery of a new strain of coronavirus, lockdown and other restrictions, government policies, and information related to the vaccine development for the same. In this scenario, analysis of emergent and widely reported topics/themes/issues and associated sentiments from various countries can help us better understand the COVID-19 pandemic. In our research, the database of more than 100,000 COVID-19 news headlines and articles were analyzed using top2vec (for topic modeling) and RoBERTa (for sentiment classification and analysis). Our topic modeling results highlighted that education, economy, US, and sports are some of the most common and widely reported themes across UK, India, Japan, South Korea. Further, our sentiment classification model achieved 90% validation accuracy and the analysis showed that the worst affected country, i.e. the UK (in our dataset) also has the highest percentage of negative sentiment.

Research Square (Research Square), Nov 29, 2022

The popularity of the instant messaging app Telegram in Ukraine and Russia was strong even before... more The popularity of the instant messaging app Telegram in Ukraine and Russia was strong even before the still-ongoing Russian invasion of Ukraine. However, since 24 February 2022 (when the Russian invasion began), it has seen huge increases in subscribers and even become the primary communication and news source in Ukraine. In this exploratory research, we analysed Telegram channels from both Ukraine (@UkraineNow-the official channel of the Ukrainian government, and @V_Zelen-skiy_official-the official channel of Ukraine's President Volodymyr Zelenskyy) and Russia (@rt_russian-the official channel of the news network RT) to discern the content of posts during this invasion. Our analysis of 37,172 posts in total showed that while @UkraineNow is particularly being used to communicate invasion-related news, @rt_russian is working as merely an extension of RT, which is part of the pro-Kremlin propaganda and disinformation ecosystem. However, Zelenskyy has opted for a completely different approach: he has used his Telegram channel to encourage Ukrainians and garner support from the World. The present conflict is at a critical juncture, and our timely research seeks to determine how both countries' governments are utilizing Telegram as a weapon for the information war and what impact this has on ground.

Frontiers in Fake Media Generation and Detection

Hindutva, the core political ideology of India's current ruling party, the Bharatiya Janata P... more Hindutva, the core political ideology of India's current ruling party, the Bharatiya Janata Party (BJP), seeks to transform constitutionally secular India into a Hindu Rashtra (`Hindu nation'). Although Hindutva has all of the features of right-wing extremism (RWE), it is nevertheless viewed as a sociopolitical phenomenon due to the Eurocentric nature of RWE discourse. Recent theoretical and analytical research has sought to showcase the similarity between RWE and Hindutva, whereas empirical research on their relationship has not been conducted. To fill that gap, in our study we collected 15 million tweets, and in network analysis, identified prominent themes of RWE, including exclusionary nationalism, conspiracy theories, and anti-minority violence and hate speech among the supporters of Hindutva and BJP. Furthermore, our toxicity analysis performed to understand which themes produced higher levels of toxicity, we found that Hindi-language tweets related to conspiracy theor...

The popularity of the instant messaging app Telegram in Ukraine and Russia was strong even before... more The popularity of the instant messaging app Telegram in Ukraine and Russia was strong even before the still-ongoing Russian invasion of Ukraine. However, since 24 February 2022 (when the Russian invasion began), it has seen huge increases in subscribers and even become the primary communication and news source in Ukraine. In this exploratory research, we analyzed Telegram channels from both Ukraine (@UkraineNow — the official channel of the Ukrainian government, and @V_Zelenskiy_official — the official channel of Volodymyr Zelenskyy) and Russia (@rt_russian — the official channel of the news network RT) to discern the content of posts during this invasion. Our analysis of 37,172 posts in total showed that while @UkraineNow is particularly being used to communicate invasion-related news, @rt_russian is working as merely an extension of RT, which is part of the pro-Kremlin propaganda and disinformation ecosystem. However, Zelenskyy has opted for a completely different approach: he has...

SSRN Electronic Journal, 2022

Despite the widespread global concerns on the potential detrimental effects of misinformation on ... more Despite the widespread global concerns on the potential detrimental effects of misinformation on democracy, the vast majority of studies still focus on Western countries. As a result, we disproportionately know more about wealthy countries characterized by lasting democratic traditions and pluralistic media systems than what we know about contexts where these institutions are yonder and more fragile. This work contributes to filling this gap by applying to the case of India an approach to map and study networks of coordinated social media accounts that spread problematic health-related content on Indian Facebook and Instagram.

During the initial months of the COVID-19 pandemic, the world saw lots of incidents of hate speec... more During the initial months of the COVID-19 pandemic, the world saw lots of incidents of hate speech, xenophobia, and discrimination where a specific community or people were targeted or accused of being spreaders of the Coronavirus disease. One such prominent episode happened in India, where the Muslim community was targeted for spreading COVID-19. This episode later became known as the “Tablighi Jamaat Controversy” (TJC). We analyzed Facebook posts by public groups during the five months (March to August 2020) that this furor raged to find the major actors and their link-sharing behavior and the presence of (if any) fake news and misinformation. We found that Islamophobic hate speech was spread by the Facebook groups that are Pro-BJP (Bhartiya Janta Party – the leading party in the present Indian government) and have a right-wing ideology, while other groups (anti-hate) were countering the hate. We also found that the hate spreaders were extremely active (three times faster) in shar...

During the initial months of the COVID-19 pandemic, the world saw lots of incidents of hate speec... more During the initial months of the COVID-19 pandemic, the world saw lots of incidents of hate speech, xenophobia, and discrimination where a specific community or people were targeted or accused of being spreaders of the Coronavirus disease. One such prominent episode happened in India, where the Muslim community was targeted for spreading COVID-19. This episode later became known as the “Tablighi Jamaat Controversy” (TJC). We analyzed Facebook posts by public groups during the five months (March to August 2020) that this furor raged to find the major actors and their link-sharing behavior and the presence of (if any) fake news and misinformation. We found that Islamophobic hate speech was spread by the Facebook groups that are Pro-BJP (Bhartiya Janta Party – the leading party in the present Indian government) and have a right-wing ideology, while other groups (anti-hate) were countering the hate. We also found that the hate spreaders were extremely active (three times faster) in shar...

International Journal of Semantic Computing

Cybersecurity is becoming indispensable for everyone and everything in the times of the Internet ... more Cybersecurity is becoming indispensable for everyone and everything in the times of the Internet of Things (IoT) revolution. Every aspect of human society — be it political, financial, technological, or cultural — is affected by cyber-attacks or incidents in one way or another. Newspapers are an excellent source that perfectly captures this web of cybersecurity. By implementing various NLP techniques such as tf-idf, word embedding and sentiment analysis (SA) (machine learning method), this research will examine the cybersecurity-related articles from 18 major newspapers (English language online version) from six countries (three newspapers from each country) collected within one year from April 2018 till March 2019. The first objective is to extract the crucial events from each country, which we will achieve by our first step — ‘information extraction.’ The next objective is to find out what kind of sentiments those crucial issues garnered, which we will accomplish from our second s...

CHI Conference on Human Factors in Computing Systems

Deepfakes are synthetic content generated using advanced deep learning and AI technologies. The a... more Deepfakes are synthetic content generated using advanced deep learning and AI technologies. The advancement of technology has created opportunities for anyone to create and share deepfakes Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

Digital Scholarship in the Humanities

For Japan—a country that has always been described with virtually no major natural resources such... more For Japan—a country that has always been described with virtually no major natural resources such as oil, gas, and coal—the Middle Eastern region has a special place in its economic and foreign policy. In 2017, 39% of Japan’s energy came from oil, and 87% of Japan’s imported oil came from the Middle East, predominantly Saudi Arabia and the UAE. The above facts are enough to discern the critical significance of the Middle Eastern region for Japan. For Japan to have an unhindered supply of oil and other natural resources, it is pertinent that this region remains peaceful. In this scenario, the Middle East-related articles in Japan’s newspapers can help understand Japan’s perspective towards the Middle East. This paper would first apply the topic modelling approach non-negative matrix factorization (NMF) on Middle East-related articles from three newspapers of Japan. After discovering crucial topics, we would utilize traditional supervised machine learning algorithms to determine the o...

ArXiv, 2021

Currently, the significance of social media in disseminating noteworthy information on topics suc... more Currently, the significance of social media in disseminating noteworthy information on topics such as health, politics, and the economy is indisputable. During the COVID-19 pandemic, anti-vaxxers use social media to distribute fake news and anxiety-provoking information about the vaccine, which may harm the public. Here, we characterize the psycho-linguistic features of anti-vaxxers on the online social network Twitter. For this, we collected COVID-19 related tweets from February 2020 to June 2021 to analyse vaccination stance, linguistic features, and social network characteristics. Our results demonstrated that, compared to pro-vaxxers, anti-vaxxers tend to have more negative emotions, narrative thinking, and worse moral tendencies. This study can advance our understanding of the online anti-vaccination movement, and become critical for social media management and policy action during and after the pandemic.

This dataset is consist news articles related to COVID-19 from UK, India, Japan and South Korea n... more This dataset is consist news articles related to COVID-19 from UK, India, Japan and South Korea newspapers.

Globalization has connected the nations of the world in a way never seen before. Happenings or ev... more Globalization has connected the nations of the world in a way never seen before. Happenings or events in one nation has the potential to impact other nations also. By collecting and analyzing cybersecurity-related articles from three major national newspapers of Japan, this research is trying to find out and understand Japan’s newspaper reporting on the cybersecurity issue. Content analysis of those cybersecurity-related articles is used to find critical themes and patterns. The content analysis found that the contention over 5G between the U.S. and China is the most critical issue in Japanese newspapers. From an international relations perspective, the issue between the U.S. and China over 5G is an adverse event represented in newspapers with words such as tussle, tech-war, and contention, but by performing sentiment analysis (content-based analysis) on the articles only related to Huawei, this research tried to find how machine categorize this issue. Then this research critically ...

Recent advancements in the field of Information Technology (IT) have not only changed the way peo... more Recent advancements in the field of Information Technology (IT) have not only changed the way people consume news but also made it possible for researchers to analyze a plethora of news, especially when the headlines are changing every minute. Big data, Natural Language Processing (NLP) and Machine Learning (ML) techniques are becoming staple for researchers of every domain to discover patterns and themes in the vast amount of data. This research would utilize NPL and ML techniques to analyze cybersecurity-related newspaper articles of major newspapers (digital version) from Japan and the US. Japan and the US are close allies, and they are collaborating in the field of cybersecurity owing to its rising significance for nations. However, as the demography, culture, and political behavior are different in both countries, it would be fascinating and very critical to analyze how newspapers from both countries are dealing with cybersecurity issues.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is wreaking havoc. This virus has in... more Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is wreaking havoc. This virus has infected more than 62.01 million and killed around 1.44 million people worldwide in less than a year. For the past 11 months, this is the most critical issue that the world is dealing with. Hence, there is a rapid accumulation of coronavirus-related news. Natural language processing (NLP) and machine learning (ML) methods such as topic modeling receive much attention because of their ability to discover hidden themes and issues from large unstructured text data. We collected 63,424 COVID-19/coronavirus themed news articles from Japanese and Indian English newspapers and applied the recently proposed Top2Vec model to analyze and extract major topics. Our research finds out that both countries’ media reported heavily about the problems that arise due to coronavirus in sports, education, and entertainment sectors. Our findings also point out that Indian media gave very little space to the iss...

2021 International Conference on Information Networking (ICOIN)

Machine Learning (ML) and specifically Natural Language Processing (NLP) are increasingly used as... more Machine Learning (ML) and specifically Natural Language Processing (NLP) are increasingly used as tools in the cybersecurity world. These NLP tools bring new capabilities that support both defenders and attackers in their activities, whether it is risk scenarios such as events and threats or security operations. Ours is a unique case study as we are investigating cybersecurity news on a national and global level. This large study covered six countries and 18 major newspapers and analyzed thousands of cybersecurity articles using the Nonnegative Matrix Factorization (NMF) topic modeling method. News making and policymaking complement each other in forming national identities. This research aims to provide the foundation for the field of Cybersecurity in this direction. Our results showed the US dominance and its significance for other countries. This research also highlighted that much of the US media’s cybersecurity reporting focuses on domestic issues, unlike other nations.

IEEE Access

Newspapers are very important for a society as they inform citizens about the events around them ... more Newspapers are very important for a society as they inform citizens about the events around them and how they can impact their life. Their importance becomes more crucial and indispensable in the times of health crisis such as the current COVID-19 pandemic. Since the starting of this pandemic newspapers are providing rich information to the public about various issues such as the discovery of a new strain of coronavirus, lockdown and other restrictions, government policies, and information related to the vaccine development for the same. In this scenario, analysis of emergent and widely reported topics/themes/issues and associated sentiments from various countries can help us better understand the COVID-19 pandemic. In our research, the database of more than 100,000 COVID-19 news headlines and articles were analyzed using top2vec (for topic modeling) and RoBERTa (for sentiment classification and analysis). Our topic modeling results highlighted that education, economy, US, and sports are some of the most common and widely reported themes across UK, India, Japan, South Korea. Further, our sentiment classification model achieved 90% validation accuracy and the analysis showed that the worst affected country, i.e. the UK (in our dataset) also has the highest percentage of negative sentiment.