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During a 2025 survey, ** percent of respondents from Nigeria stated that they used social media as a source of news. In comparison, just ** percent of Japanese respondents said the same. Large portions of social media users around the world admit that they do not trust social platforms either as media sources or as a way to get news, and yet they continue to access such networks on a daily basis. Social media: trust and consumption Despite the majority of adults surveyed in each country reporting that they used social networks to keep up to date with news and current affairs, a 2018 study showed that social media is the least trusted news source in the world. Less than ** percent of adults in Europe considered social networks to be trustworthy in this respect, yet more than ** percent of adults in Portugal, Poland, Romania, Hungary, Bulgaria, Slovakia and Croatia said that they got their news on social media. What is clear is that we live in an era where social media is such an enormous part of daily life that consumers will still use it in spite of their doubts or reservations. Concerns about fake news and propaganda on social media have not stopped billions of users accessing their favorite networks on a daily basis. Most Millennials in the United States use social media for news every day, and younger consumers in European countries are much more likely to use social networks for national political news than their older peers. Like it or not, reading news on social is fast becoming the norm for younger generations, and this form of news consumption will likely increase further regardless of whether consumers fully trust their chosen network or not.

According to a survey conducted in May 2025, 56 percent of adults in the United States said they actively seek out news, while 35 percent reported that news usually comes to them. A smaller share were unsure about their news consumption habits.

In May 2025, a survey asked U.S. adults how they feel while consuming news. The results indicate that a majority feel informed, with 53 percent saying that news generally makes them feel this way. At the same time, 43 percent reported feeling angry, and 32 percent said they feel depressed when consuming news. In contrast, only 16 percent described feeling hopeful. These findings highlight that while staying informed is a major benefit of news consumption, negative emotional reactions—such as anger and depression—are also very common among Americans.

Times of India Headlines Analysis

Sentiment and Word Trends since Jan 2020

By Priyanka Dobhal [source]

About this dataset

This dataset features a collection of headlines from the Times of India newspaper, along with detailed sentiment scores for each article. With this data, you can analyze trends in news reporting and sentiments of these headlines to gain new insight into the content and topics covered by the Times of India. Analyze the words linked with each headline, as well as its positive, negative, neutral, and compound sentiment scores to gain a deeper understanding of what is being reported today by this influential news organization

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How to use the dataset

This dataset provides a comprehensive analysis of headlines from the Times of India since January 2020. This includes sentiment scores for each headline and the associated words used, in addition to the headline’s URL link and date it was published.

The dataset can be used to understand public opinion responses related to news stories published by the Times of India in a given time frame, such as any trends regarding specific topics or certain countries. It is also possible to compare sentiment scores with other media sources to observe how sentiment towards different topics changes over time.

To analyze this data you can use various statistical methods such as looking at mean values, median values, percentiles, quartiles etc., or you can use more comprehensive methods such as natural language processing (NLP). NLP enables further exploration into the headlines using machine learning models like topic modelling or clustering algorithms which will give further insights into topics discussed in each headline. Additionally you can visualize your results on charts and graphs so that patterns are easier to identify at a glance

Research Ideas

• Using the sentiment scores for each headline, create a content analysis to study how the sentiment of the news has changed over time.
• Utilize the headline link and URL columns to track reader engagement with news content on a given day or over a specific period.
• Utilize Natural Language Processing techniques to identify and analyze recurring themes in headlines from 2020 in order to identify popular topics and sources of trending news stories in India

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: Times_of_India_Healines_since_jan_2020_score.csv | Column name | Description | |:------------------|:--------------------------------------------------------------------------------------------------------------------------| | S_No | Unique numerical identifier for each headline. (Integer) | | URL | The URL associated with each headline. (String) | | Date | Date of publication for the story. (Date) | | Headline | Title of the news article provided by Times Of India newspaper headliner. (String) | | Headline Link | Link to the news article associated with this headline. (String) | | Positive | Sentiment score between 0 and 1 indicating the degree of positive sentiment in the headline. (Float) | | Negative | Sentiment score between 0 and 1 indicating the degree of negative sentiment in the headline. (Float) | | Neutral | Sentiment score between 0 and 1 indicating the degree of neutral sentiment in the headline. (Float) | | Compound | Overall sentiment score for each headline ranging from -1 (most extreme negative) to + 1 (most extreme positive). (Float) |

File: Times_of_India_Healines_words.csv | Column name | Description | |:------------------|:-----------------------------------------------------------------------------------| | S_No | Unique numerical identifier for each headline. (Integer) | | URL ...

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TL;DR

Our free COVID-19 Stats and New API lets you send a web-based query to Smartable AI and get back details about global and regional coronavirus data, including latest numbers, historic values, and geo-breakdowns. It is the same API that powers our popular COVID-19 stats pages. Developers can take the returned information and display it in their own tools, apps and visualizations. Different from other coronavirus data sources that produce breaking changes from time to time, the data from our API are more stable, **detailed **and close to real-time, as we leverage AI to gather information from many credible sources. With a few clicks in our API try-it experience, developers can get it running quickly and unleash their creativity.

Click here to get started

Our Mission

“We’re not just fighting an epidemic; we’re fighting an infodemic” – WHO Director-General Tedros Adhanom Ghebreyesus

In Smartable AI, our mission is to use AI to help you be smart in this infodemic world. Information is exploded, and mis-information has impacted the decisions of governments, businesses, and citizens around the world, as well as individuals’ lives. In 2018, The World Economic Forum identified it as one of the top 10 global risks. In a recent study, the economic impact has been estimated to be upwards of 80-100 Billion Dollars. Everything we do is focused on fighting misinformation, curating quality content, putting information in order and leveraging technology to bring clean, organized information through our APIs. Everyone wins when they can make sense of the world around them.

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The coronavirus stats and news API offers the latest and historic COVID-19 stats and news information per country or state. The stats are refreshed every hour using credible data sources, including the country/state’s official government websites, data available on wikipedia pages, latest news reports, Johns Hopkins University CSSE 2019-nCoV Dashboard, WHO Situation Reports, CDC Situation Updates, and DXY.cn.

The API takes the location ISO code as input (e.g. US, US-MA), and returns the latest numbers (confirmed, deaths, recovered), the delta from yesterday, the full history in that location, and geo-breakdown when applicable. We offer detailed API documentation, a try-it experience, and code examples in many different programming languages.

https://smartable.azureedge.net/media/2020/03/coronavirus-api-documentation.webp" alt="API Documentation">

We upload a daily dump of the data in the csv format here.

We want it to be a collaborative effort. If you have any additional requirements for the API or observe anything wrong with the data, we welcome you to report issues in our GitHub account. The team will jump in right away. All our team members are ex-Microsoft employees, so you can trust the quality of support, I guess 🙂

Our Example Apps powered by the API

We have developed two example apps by using the API.

• COVID-19 Live Stats+News
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