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In this study, we developed an Emotion Detection (ED) model for Brazilian Portuguese social media comments and used it to analyze emotion distribution in replies to COVID-19-related news on Twitter. We translated the GoEmotions dataset into ...

Online news article recommendations are typically of the ‘more like this’ type, generated by similarity functions. Across three studies, we examined the representativeness of different similarity functions for news item retrieval, by comparing ...$\mathrm{}$$\mathrm{}$$\mathrm{}$

Coronavirus disease 2019 (COVID-19) pandemic has produced a global health crisis that has had a deep impact on the way we perceive our world and everyday lives. Not only the spread rate of contagion and patterns of transmission endangered our sense of ...

One of the most significant challenges in stock market forecasting is that the majority of stock price analysis and prediction models based on quantitative data rely on stock trends as their primary metric. These metrics may exhibit good intra-day ...

Predicting the political bias of news headlines is a challenging task that becomes even more challenging in a multilingual setting with low-resource languages. To deal with this, we propose to utilise Inferential Commonsense Knowledge ...

• Utilise COMET’s inferential commonsense knowledge to comprehend news headlines.

Cryptocurrencies have increasingly been traded against fiat currencies and as a result, governments globally have been trying to regulate these largely decentralized currencies. In this study, event study methodology has been used to evaluate the effect ...

We evaluate homophily and heterophily among ideological and demographic groups in a typical opinion formation context: online discussions of current news. We analyze user interactions across five years in the r/news community on Reddit, one of the most ...

This study examined the role of social media in activating civic engagement and political participation among Nigerian citizens by age. It used a substantial secondary data set from the Afrobarometer Index (N=45,823 from 34 African countries; N=1,600 ...

ICT platforms for news production, distribution, and consumption must exploit the ever-growing availability of digital data. These data originate from different sources and in different formats; they arrive at different velocities and in different ...

The company Altmetric is often used to collect mentions of research in online news stories, yet there have been concerns about the quality of this data. This study investigates these concerns. Using a manual content analysis of 400 news stories as ...

Tracking news stories in documents is a way to deal with the large amount of information that surrounds us everyday, to reduce the noise and to detect emergent topics in news. Since the Covid-19 outbreak, the world has known a new problem: ...

The increase in the consumption of digital formats has, in many cases, been a penalty for traditional media companies. In the adaptation to digital, the transformation of written news into audio formats, that guarantee spatio-temporal flexibility in its ...

What do news landscapes look and sound like? And how can we transform them into tangible objects to see clusters of over-reporting, or to hear the missing voices in under-reported topics? A new artwork called Fragile Perspectives was developed to ...

• Fuzzy rule-based prediction system with a news affect component.
• Highly interpretable trading strategy in terms of rule complexity.
• One- and five-days-ahead gold price predictions.
• Outperforms state-of-the-art models in terms ...

Because of gold’s value, systems for predicting its price have attracted extensive interest in the scientific and industrial communities. Diverse artificial intelligence methods outperform traditional statistical methods in predicting short- and ...

We introduce FinLin, a novel corpus containing investor reports, company reports, news articles, and microblogs from StockTwits, targeting multiple entities stemming from the automobile industry and covering a 3-month period. FinLin was annotated ...

Nowadays, more and more news readers read news online where they have access to millions of news articles from multiple sources. In order to help users find the right and relevant content, news recommender systems (NRS) are developed to relieve ...

News is an essential resource for understanding politics, economics, local communities, etc. Readers of news articles might browse the text quickly or read thoroughly. In this study, we analyze the contents of news articles and propose a method for ...

Extract summarization algorithms help identify significant information from the news by extracting meaningful sentences from the original text. The information background existing at the time of the news release often significantly affects its ...

Extracting meaningful social networks from a large corpus of news articles is challenging. This paper presents a network embedding technique which uses the content of texts as context information for relationships among persons referenced in ...

Determining the names of companies in the news text is an important task in predicting changes in the prices of companies’ shares. There is a large number of works devoted to this problem, a large number of algorithms have been created. On the ...