newspaper comparison research paper

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Methodological note, find out more, newspapers fact sheet.

Newspapers are a critical part of the American news landscape, but they have been hit hard as more and more Americans consume news digitally. The industry’s financial fortunes and subscriber base have been in decline since the mid-2000s, and their website audience traffic has begun to decline as well. Explore the patterns and longitudinal data of U.S. newspapers below.

In 2022, estimated total U.S. daily newspaper circulation (print and digital combined) was 20.9 million for both weekday and Sunday, down 8% and 10% respectively from 2021.

Note: To determine totals for 2015 onward, researchers analyzed the year-over-year change in total weekday and Sunday circulation using AAM data and applied these percent changes to the previous year’s total. Only those daily U.S. newspapers that report to AAM are included. Affiliated publications are not included in the analysis. Weekday circulation only includes those publications reporting a Monday-Friday average. Comparisons are either between the three-month averages for the period ending Dec. 31 of the given year and the same period of the previous year (2015-2019), the six-month period ending Sept. 30 and the three-month period ending Sept. 30 of the previous year (2020), or the six-month period ending Sept. 30 of the given year and the same period of the previous year (2021-2022).

Source: Editor & Publisher (through 2014); estimate based on Pew Research Center analysis of Alliance for Audited Media data (2015-2022).

(Note that the Alliance for Audited Media (AAM), the source of this circulation data and the group that audits the circulation figures of many of the largest North American newspapers and other publications, changed their reporting period in 2020 from a three-month period to a six-month period. Additional details about how the circulation estimate is calculated can be found in the  methodological note  below.)

Within this total circulation figure, weekday print circulation decreased 13% and Sunday print circulation decreased 16% from the previous year.

Digital circulation is more difficult to gauge. Using only the AAM data, digital circulation in 2022 is projected to have remained relatively stable. But three of the highest-circulation daily papers in the U.S. – The New York Times, The Wall Street Journal and The Washington Post – have in recent years not fully reported their digital circulation to AAM. The Times and the Journal provide data on digital subscriptions in publicly available reports, but since this is not the same as circulation and may not be counted under the same rules used by AAM, these independently produced figures cannot easily be merged with the AAM data. If these independently produced figures were included with the AAM data in both 2021 and 2022, weekday digital circulation would have risen sharply, by 22%.

Note: Researchers analyzed the year-over-year change in total weekday circulation using AAM data and applied these percent changes to the previous year’s total. Only those daily U.S. newspapers that report to AAM are included. Affiliated publications are not included in the analysis. Weekday circulation only includes those publications reporting a Monday-Friday average. Comparisons are either between the three-month averages for the period ending Dec. 31 of the given year and the same period of the previous year (2016-2019), the six-month period ending Sept. 30 and the three-month period ending Sept. 30 of the previous year (2020), or the six-month period ending Sept. 30 of the given year and the same period of the previous year (2021-2022).

Source: Estimate based on Pew Research Center analysis of Alliance for Audited Media data and subscription data from SEC filings and audited reports.

The addition of these figures also changes the overall picture for combined print and digital circulation. Before 2020, including these subscription numbers with the AAM circulation data would not have changed the overall circulation picture, as total circulation would still decline. From 2020 onward, however, including the Times’ and the Journal’s digital subscribers reverses the trend. In 2022, total weekday circulation would rise by 12% – not fall by 8%, as is the case when looking strictly at the AAM data. For comparison, the chart above shows estimated total weekday circulation using just the AAM data and when the digital subscriber numbers from the Times and Journal are included over the past seven years. For more details on how this affects our estimates and conclusions, read  this post from 2020 on our Decoded blog.

Note: For each year, the average traffic for each website for October/November/December was calculated; the data point represents the overall average of those numbers. Analysis is of the top 49 newspapers by average Sunday circulation for Q3 2015-2019 and the six-month period ending Sept. 30 for 2020 onward, according to Alliance for Audited Media data, with the addition of The Wall Street Journal. For each newspaper, the Comscore entity matching its homepage URL was analyzed.

Source: Comscore Media Metrix® Multi-Platform, US, Unique Visitors, October-December 2014-2022.

Gauging digital audience for the entire newspaper industry is difficult since many daily newspapers do not receive enough traffic to their websites to be measured by Comscore, the data source relied on here. Thus, the figures offered above reflect the top 50 U.S. daily newspapers based on circulation. In the fourth quarter of 2022, there were an average 8.8 million monthly unique visitors (across all devices) for these top 50 newspapers. This is down 20% from 2021, which itself was a 20% decrease from 2020.

(The list of top 50 papers is based on Sunday circulation but includes The Wall Street Journal, which does not report Sunday circulation to AAM. It also includes The Washington Post and The New York Times, which make the top 50 even though they do not fully report their digital circulation to AAM. For more details and the full list of newspapers, read our  methodology .)

Note: For each year, the average minutes per visit for each website for October/November/December was calculated; the data point represents the overall average of those numbers. Analysis is of the top 49 newspapers by average Sunday circulation for Q3 2015-2019 and the six-month period ending Sept. 30 for 2020 onward, according to Alliance for Audited Media data, with the addition of The Wall Street Journal. For each newspaper, the Comscore entity matching its homepage URL was analyzed.

Source: Comscore Media Metrix® Multi-Platform, US, Average Minutes Per Visit, October-December 2014-2022.

Average minutes per visit for the top 50 U.S. daily newspapers, based on circulation, was just under 1 minute and 30 seconds in Q4 2022. This represents a 43% decline from when we first began tracking this in Q4 2014, when the average minutes per visit was just over 2 minutes and 30 seconds.

The total estimated advertising revenue for the newspaper industry in 2022 was $9.8 billion, based on the Center’s analysis of financial statements for publicly traded newspaper companies. This is down 5% from 2021, a slight drop. Total estimated circulation revenue was $11.6 billion, compared with $11.5 billion in 2020.

Source: News Media Alliance, formerly Newspaper Association of America (through 2012); Pew Research Center analysis of year-end SEC filings of publicly traded newspaper companies (2013-2022).

In the chart above, data through 2012 comes from the trade group formerly known as the Newspaper Association of America (NAA), now known as the News Media Alliance (NMA). Data from 2013 onward is based on the Center’s analysis of financial statements from publicly traded U.S. newspaper companies, which in 2022 numbered four and accounted for about 300 U.S. daily newspapers, from large national papers to midsize metro dailies and local papers.

From 2013 onward, the year-over-year percentage change in advertising and circulation revenue for these companies is calculated and then applied to the previous year’s revenue totals as reported by the NMA/NAA. In testing this method, changes from 2006 through 2012 generally matched those as reported by the NMA/NAA; for more details, read our  2016 report .

Source: Pew Research Center analysis of year-end SEC filings for publicly traded newspaper companies that break out digital advertising revenue for each year.

Digital advertising accounted for 48% of newspaper advertising revenue in 2022, based on this analysis of publicly traded newspaper companies. This follows a steady increase from 17% in 2011, the first year it was possible to perform this analysis.

In this fact sheet, circulation data through 2014 is from Editor & Publisher, which was published on the website of the News Media Alliance (NMA), known at the time as the Newspaper Association of America (NAA). The NMA no longer supplies this data, so the Center determined the year-over-year change in total circulation for those daily U.S. newspapers that report to the Alliance for Audited Media and meet certain criteria. This percentage change was then applied to the total circulation from the prior year – thus the use of the term “estimated total circulation.” This technique is also used to create the revenue estimates, using the financial statements of publicly traded newspaper companies as the data source.

This fact sheet was compiled by Research Assistants  Sarah Naseer  and  Christopher St. Aubin .

Read the  methodology .

Pew Research Center is a subsidiary of The Pew Charitable Trusts, its primary funder. This is the latest report in Pew Research Center’s ongoing investigation of the state of news, information and journalism in the digital age, a research program funded by The Pew Charitable Trusts, with generous support from the John S. and James L. Knight Foundation.

Find more in-depth explorations of U.S. newspapers by following the links below:

• After increasing in 2020, layoffs at large U.S. newspapers and digital news sites declined in 2021 , Oct. 13, 2022
• News Platform Fact Sheet , Sept. 20, 2022
• Local Newspapers Fact Sheet , May 26, 2022
• U.S. newsroom employment has fallen 26% since 2008 , July 13, 2021
• A third of large U.S. newspapers experienced layoffs in 2020, more than in 2019 , May 21, 2021
• Coronavirus-Driven Downturn Hits Newspapers Hard as TV News Thrives , Oct. 29, 2020
• Nearly 2,800 newspaper companies received paycheck protection loans, and most were under $150K , Oct. 29, 2020
• Americans’ main sources for political news vary by party and age , April 1, 2020
• Black and white Democrats differ in their media diets, assessments of primaries , March 11, 2020
• Fast facts about the newspaper industry’s financial struggles as McClatchy files for bankruptcy , Feb. 14, 2020
• U.S. Media Polarization and the 2020 Election: A Nation Divided , Jan. 24, 2020
• For Local News, Americans Embrace Digital but Still Want Strong Community Connection , March 26, 2019
• What are the local news dynamics in your city? , March 26, 2019

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ABOUT PEW RESEARCH CENTER  Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of  The Pew Charitable Trusts .

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Why Use Newspapers?

Finding a specific newspaper, finding articles if you have a citation, finding articles on a topic, finding article full text.

• Newspapers in the Library Collection
• Newspaper Websites

Newspaper articles can provide a useful source of information, serving as a primary source of information about historical and current events. Some of the benefits of using newspaper articles as primary sources include:

• seeing how people viewed an event when it happened;
• providing multiple points of view about an issue, including a comparison of the United States and international views;
• permitting researchers to trace the historical development of subjects over time;
• examining issues in the context of their time (by seeing how stories about an issue relate to other stories, or by examining the type of coverage provided);
• giving a snapshot of a time period detailing how people lived, and what they purchased, etc. which is helpful for writers, playwrights, historians, etc.

Because newspapers also contain commentaries or retrospective articles about events, they can also serve as a secondary source. (Modified from Why Use Newspapers? - OhioState University)

To find a specific newspaper, try the following:

1. On the library home page in the search box click the Journals tab. Type the newspaper title.

The search will return results for titles starting with the words you typed. If you want to search for the exact tile or are not sure of the the complete title, use the E-Journals Search (link below the box). From the drop-down menu you can select "Title contains all words" if you are not sure in what order the words appear in the title or "Title equals" (the latter would be useful for short titles like "Time" or "Times").

2. For titles not available online, click "Print Journals" under the search box for journal searches. This will take you to the library catalog. Click on the "Title" tab. Do a catalog TITLE search for the newspaper title. It is useful to limit your search to Periodicals/Serials.

Results list may include several entries for different versions of the title and various formats (print, microfilm, and electronic). If you are confused, ask a librarian for help. For your convenience, information about popular newspapers in our collection is provided in this guide.

Library records may include information about current print holdings and microforms, as well as links to online content. Please note that the catalog does NOT have links to ALL newspapers available online, use the e-journals search for this.

First, determine if the issue of the newspaper is available online.

Method 1 . Search for the article title in quotation marks (and author's name, if the title is common) in the red search box on the home page (under the "Articles" tab).

A successful search will include a link to the article full text.

Method 2. Use the E-Journals search to see if the issue you need is available online. This method is more comprehensive, because it will find ALL of library electronic subscriptions. It also helps when a link in Method 1 does not work.

In the results list find a database that covers the period when the article of interest was published.

You can click "Look up Article" or go to the database. Most databases will allow you to browse to the volume and issue or search for the article.

If the article is not available online or you need to see the article as it was published with original graphics, do a catalog search for the newspaper title in the library catalog as described above . Important note: search for the newspaper title, NOT the article title.

• Start with searching Summon . After you enter your search terms and get results, you will be able to refine you search by Content - Newspapers . You may also select a date range for the articles.

• Search one of the general newspaper databases . You should also be able to filter your results to newspaper content and specify dates.
• Many subject guides provide information on newspapers in the discipline.
• Ask your subject librarian for assistance.

Please note that newspaper databases come in different formats.

Digital archive databases provide scanned reproductions of original newspaper pages (the full-text and any accompanying graphics).

Full-text databases provide the complete text of newspaper articles (but not accompanying graphics).

Index only databases provide citations (references) to newspaper articles. You can use these to identify the publication date and page number details for specific articles.

Therefore you may still need to use digital or traditional microfilms to view the articles you found using an online database.

If you working with newspapers not available online, you may need to use an index, which may be available in print or on a microfilm. Ask for help at the desk or via an online form .

Remember that if we don't have access to an article you can request it through interlibrary loan (ILLiad) .

(Modified from Newspapers & news services: Finding newspaper articles on a topic - University of Wollongong)

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• Last Updated: Mar 11, 2024 11:25 AM
• URL: https://guides.libraries.uc.edu/newspapers

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Types of Sources - What's the Difference

• Types of Sources (video)
• Primary, Secondary, Tertiary
• Scholarly / Peer-reviewed
• Trade / Professional
• General Interest
• Popular / Sensational

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Using articles to support or refute a thesis statement or hypothesis is common practice for research projects. The difference between the types of articles is significant and your topic and research focus determines the suitability of which type of source you should use. Scholarly journals, trade publications, and general interest magazines are important sources of information. The chart below highlights the difference between types of articles.

• Types of Articles Comparison Table Compare differences between scholarly, trade, popular, and news articles.

Article Comparison Table (text)

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• Last Updated: Jul 15, 2024 12:56 PM
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Writing a Paper: Comparing & Contrasting

A compare and contrast paper discusses the similarities and differences between two or more topics. The paper should contain an introduction with a thesis statement, a body where the comparisons and contrasts are discussed, and a conclusion.

Address Both Similarities and Differences

Because this is a compare and contrast paper, both the similarities and differences should be discussed. This will require analysis on your part, as some topics will appear to be quite similar, and you will have to work to find the differing elements.

Make Sure You Have a Clear Thesis Statement

Just like any other essay, a compare and contrast essay needs a thesis statement. The thesis statement should not only tell your reader what you will do, but it should also address the purpose and importance of comparing and contrasting the material.

Use Clear Transitions

Transitions are important in compare and contrast essays, where you will be moving frequently between different topics or perspectives.

• Examples of transitions and phrases for comparisons: as well, similar to, consistent with, likewise, too
• Examples of transitions and phrases for contrasts: on the other hand, however, although, differs, conversely, rather than.

For more information, check out our transitions page.

Structure Your Paper

Consider how you will present the information. You could present all of the similarities first and then present all of the differences. Or you could go point by point and show the similarity and difference of one point, then the similarity and difference for another point, and so on.

Include Analysis

It is tempting to just provide summary for this type of paper, but analysis will show the importance of the comparisons and contrasts. For instance, if you are comparing two articles on the topic of the nursing shortage, help us understand what this will achieve. Did you find consensus between the articles that will support a certain action step for people in the field? Did you find discrepancies between the two that point to the need for further investigation?

Make Analogous Comparisons

When drawing comparisons or making contrasts, be sure you are dealing with similar aspects of each item. To use an old cliché, are you comparing apples to apples?

• Example of poor comparisons: Kubista studied the effects of a later start time on high school students, but Cook used a mixed methods approach. (This example does not compare similar items. It is not a clear contrast because the sentence does not discuss the same element of the articles. It is like comparing apples to oranges.)
• Example of analogous comparisons: Cook used a mixed methods approach, whereas Kubista used only quantitative methods. (Here, methods are clearly being compared, allowing the reader to understand the distinction.

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The History of Peer Review Is More Interesting Than You Think

The term “peer review” was coined in the 1970s, but the referee principle is usually assumed to be as old as the scientific enterprise itself. (It isn’t.)

Peer review has become a cornerstone of academic publishing, a fundamental part of scholarship itself. With peer review, independent, third-party experts in the relevant field(s) assess manuscripts submitted to journals. The idea is that these expert peers referee the process, especially when it comes to technical matters that may be beyond the knowledge of editors.

“In all fields of academia, reputations and careers are now expected to be built on peer-reviewed publication; concerns with its efficacy and appropriateness thus seem to strike at the heart of scholarship,” write historians Noah Moxham and Aileen Fyfe .

The peer review system, continue Moxham and Fyfe, is “crucial to building the reputation both of individual scientists and of the scientific enterprise at large” because the process

is believed to certify the quality and reliability of research findings. It promises supposedly impartial evaluation of research, through close scrutiny by specialists, and is widely used by journal editors, grant-making bodies, and government.

As with any human enterprise, peer review is far from foolproof . Errors and downright frauds have made it through the process. In addition, as Moxham and Fyfe note, there can be “inappropriate bias due to the social dynamics of the process.” (Some peer review types may introduce less bias than others.)

The term “peer review” was coined in the early 1970s, but the referee principle is usually assumed to be about as old as the scientific enterprise itself, dating to the Royal Society of London’s Philosophical Transactions , which began publication in 1665.

Moxham and Fyfe complicate this history, using the Royal Society’s “rich archives” to trace the evolution of editorial practices at one of the earliest scientific societies.

Initially, the publication of Philosophical Transactions was a private venture managed by the Society’s secretaries. Secretary Henry Oldenburg, the first editor, ran it from 1665 to 1677, without, write Moxham and Fyfe, any “clear set of standards.”

Research sponsored by the Royal Society itself was published separately from the Transactions . In fact, the royally chartered Society had the power to license publication of books and periodicals (like the Transactions ) as “part of a wider mechanism of state censorship intended to ensure the proscription of politically seditious or religious heterodox material.” But as time passed, there wasn’t really much Society oversight over the publication at all.

The situation came to a crisis in the early 1750s, when an unsuccessful candidate for a Society fellowship raised a ruckus, conflating the separate administrations of the Society and the now rather stodgy Transactions. The bad press compelled the Society to take over financial and editorial control—by committee—of the Transactions in 1752. The editorial committee could refer submissions to fellows with particular expertise—but papers were already being vetted since they needed to be referred by fellows in the first place.

Formalization of the use of expert referees would be institutionalized by 1832. A “written report of fitness” of submissions by one or more fellows was to be made before acceptance. This followed similar procedures already introduced abroad, particularly at the Académie des sciences in Paris.

All of this, Moxham and Fyfe argue, was more about institution-building (and fortification) than what we know as peer reviewing today.

“Refereeing and associated editorial practices” were intended to “disarm specific attacks upon the eighteenth-century Society; sometimes, to protect the Society’s finances; and, by the later nineteenth century, to award prestige to members of the nascent profession of natural scientists.”

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From 1752 to 1957, the front of every Transactions included an “ Advertisement ” noting that the Society could not pretend to “answer for the certainty of the facts, or propriety of the reasonings” of the papers contained within; all that “must still rest on the credit or judgement of their respective authors.”

The twentieth century saw a plethora of independent scientific journals and an exponential increase in scientific papers. “Professional, international scientific research” burst the bounds of the old learned societies with their gentlemanly ways. In 1973, the journal Nature (founded in 1869) made refereeing standard practice, to “raise the journal above accusations of cronyism and elitism.” Since then, peer review, as it came to be called in preference to refereeing, has become universal. At least in avowed “peer-reviewed journals.”

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Dr. In Kee Kim’s Research Team Wins Best Paper Award at IEEE EDGE 2024

Dr. In Kee Kim's research team, with international collaborators, has received the Best Paper Award at IEEE EDGE 2024, held from July 7 to 13 in Shenzhen, China. The award-winning paper is titled “ Characterizing Deep Learning Model Compression with Post-Training Quantization on Accelerated Edge Devices. ”

This work is the first comprehensive characterization study of online model compression on resource-constrained edge devices. The team evaluated various deep learning models with different sizes and resource requirements, focusing on post-training quantization (PTQ) using recent NVIDIA edge devices. Their detailed analysis of performance and behavior across different precision modes highlights the challenges and opportunities of PTQ compression methods at the edge.

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International Paper (IP) Reports Q2 Earnings: What Key Metrics Have to Say

For the quarter ended June 2024, International Paper ( IP Quick Quote IP - Free Report ) reported revenue of $4.73 billion, up 1.1% over the same period last year. EPS came in at $0.55, compared to $0.59 in the year-ago quarter.

The reported revenue represents a surprise of -0.79% over the Zacks Consensus Estimate of $4.77 billion. With the consensus EPS estimate being $0.40, the EPS surprise was +37.50%.

While investors scrutinize revenue and earnings changes year-over-year and how they compare with Wall Street expectations to determine their next move, some key metrics always offer a more accurate picture of a company's financial health.

Since these metrics play a crucial role in driving the top- and bottom-line numbers, comparing them with the year-ago numbers and what analysts estimated about them helps investors better project a stock's price performance.

Here is how International Paper performed in the just reported quarter in terms of the metrics most widely monitored and projected by Wall Street analysts:

• Net Sales- Global Cellulose Fibers : $717 million versus the three-analyst average estimate of $712.46 million. The reported number represents a year-over-year change of +2.7%.
• Net Sales- Industrial Packaging : $3.93 billion compared to the $3.98 billion average estimate based on three analysts. The reported number represents a change of +1.2% year over year.
• Net Sales- Corporate and Inter-segment : $86 million versus the two-analyst average estimate of $92 million. The reported number represents a year-over-year change of -14%.
• Operating Profit- Global Cellulose Fibers : $31 million compared to the $6.41 million average estimate based on three analysts.
• Operating Profit- Industrial Packaging : $291 million versus $257.51 million estimated by three analysts on average.

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• Jul 25 2024

UK researcher wins award for outstanding review paper in advancing food science

Akinbode Adedeji , an associate professor at the  Department of Biosystems and Agricultural Engineering  (BAE) at University of Kentucky Martin-Gatton CAFE, and two fellow researchers have been awarded the prestigious Tanner Award for their seminal review paper on plant protein modification. This accolade is granted to the authors of the most cited paper by the Institute of Food Technologists (IFT) in a particular year, reflecting the significant impact and contribution to the field of food science. 

The award-winning paper titled  “Modification of Plant Proteins for Improved Functionality: A Review”  has garnered widespread recognition since its publication in Comprehensive Reviews in Food Science and Food Safety in 2021. It has been cited over 300 times, making it the most cited paper across all IFT journals that year. The work was co-authored by Adedeji along with then-UK doctoral student Felix Akharume and Rotimi Aluko from the University of Manitoba. 

What plant protein modification means for researchers? 

The review profiles various methods used to modify plant proteins, emphasizing physical, chemical and biochemical approaches. Adedeji said the work stood out for its comprehensive evaluation of techniques to enhance the quality and functional properties of plant proteins.   This included improving solubility, emulsification, gelation and foaming properties, which are crucial for developing high-quality plant-based food products. 

“Our goal was to develop a key understanding of the proteins from plant sources, focusing on their quality and functional properties,” Adedeji said. “We profiled fundamental methods for plant protein modification, which has made our paper a valuable resource for researchers globally.” 

The research was particularly timely, coinciding with the surge in demand for plant-based proteins driven by sustainability concerns and dietary shifts.  

“When we started this project in 2016, it was the onset of the plant-based protein rush,” Adedeji said. “By the time our paper was published, the food industry was actively seeking alternative protein sources. This alignment significantly contributed to the paper's high citation rate.” 

Adedeji remains optimistic about the future of plant-based proteins, despite acknowledging challenges such as replicating the sensory attributes of animal proteins and addressing the issue of ultra-processed foods.  

“The demand for sustainable protein sources ensures that plant-based proteins will remain integral to the future of food,” he said 

BAE is a partnership between Martin-Gatton CAFE and the  Stanley and Karen Pigman College of Engineering . To learn more, visit  https://www.engr.uky.edu/research-faculty/departments/biosystems-agricultural-engineering .  

This material is based upon work that is supported by the Kentucky Agricultural Experiment Station (KAES), National Institute of Food and Agriculture, U.S. Department of Agriculture, Hatch Multistate Program under award number NC1023. Any opinions, findings, conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the Department of Agriculture. 

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Enhancing the Detection of Fake News in Social Media: A Comparison of Support Vector Machine Algorithms, Hugging Face Transformers, and Passive Aggressive Classifier

• Conference paper
• First Online: 23 July 2024
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• Shamik Misra 13 ,
• Prabhat Tandon 13 &
• Purna Chandra Panda 13  

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 997))

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• International Conference on Data Management, Analytics & Innovation

In this research, we compare and contrast many different AI algorithms designed to improve the ability to spot false information on social media. In particular, it assesses the efficacy of Passive Aggressive Classifier (Crammer et al., J Mach Learn Res 7:551–585, 2006), Hugging Face (Devlin et al., Bert: pre-training of deep bidirectional transformers for language understanding. Cornell University, 2018), and Support Vector Machine Algorithms (Hearst et al., IEEE Intel Syst Appl 13:18–28, 1998; Boser et al., Proceedings of fifth annual workshop computational learning theory, pp 144–152, 1992; Schlkopf et al., Advances in kernel methods support vector learning. Mass, Cambridge, 1998; Cristianini and Shawe-Taylor, An introduction to support vector machines and other kernel-based learning methods. Cambridge University Press, 2000; Baarir et al., Algeria 2021:125–130, 2020). Amid the increasing menace of misinformation on social media, the need for effective fake news detection mechanisms cannot be overstated. The study begins with an overview of the algorithms under review, followed by an explanation of their application in fake news detection. This analysis then moves into a comparison mode, assessing each method according to several criteria including computational complexity, accuracy, precision, and recall. The research goes further into the pros and cons of each model, illuminating how well they perform with various sets of data and varieties of disinformation. In order to create reliable and accurate false news detection systems, it is important to determine which algorithms are the most successful. The results of this comparison not only add to the body of knowledge on disinformation identification, but they also provide concrete strategies for bolstering the trustworthiness of content shared on social media.

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Hearst MA, Dumais ST, Osuna E, Platt J, Scholkopf B (1998) Support vector machines. IEEE Intell Syst Appl 13(4):18–28

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Boser BE, Guyon IM, Vapnik VN (1992) A training algorithm for optimal margin classifiers. In: Proceedings of fifth annual workshop computational learning theory, pp 144–152

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Baarir NF, Djeffal A (2021) Fake news detection using machine learning. In: 2020 2nd international workshop on human-centric smart environments for health and well-being (IHSH), Boumerdes, Algeria, pp 125–130. https://doi.org/10.1109/IHSH51661.2021.9378748

Devlin J, Chang MW, Lee K, Toutanova K (2018) Bert: pre-training of deep bidirectional transformers for language understanding. Cornell University. https://arxiv.org/abs/1810.04805

Akbik A, Blythe D, Vollgraf R. Contextual string embeddings for sequence labeling. In: Proceedings of the 27th international conference on computational linguistics, pp 1638–1649. https://aclanthology.org/C18-1139/

Crammer K, Dekel O, Keshet J, Shalev-Shwartz S, Singer Y (2006) Online passive-aggressive algorithms. J Mach Learn Res 7:551–585

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Shamik Misra, Prabhat Tandon & Purna Chandra Panda

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Amlan Chakrabarti

Faculty of Computer Science, Technion—Israel Institute of Technology, Haifa, Israel

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Misra, S., Tandon, P., Panda, P.C. (2024). Enhancing the Detection of Fake News in Social Media: A Comparison of Support Vector Machine Algorithms, Hugging Face Transformers, and Passive Aggressive Classifier. In: Sharma, N., Goje, A.C., Chakrabarti, A., Bruckstein, A.M. (eds) Data Management, Analytics and Innovation. ICDMAI 2024. Lecture Notes in Networks and Systems, vol 997. Springer, Singapore. https://doi.org/10.1007/978-981-97-3242-5_14

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Study reveals how an anesthesia drug induces unconsciousness

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There are many drugs that anesthesiologists can use to induce unconsciousness in patients. Exactly how these drugs cause the brain to lose consciousness has been a longstanding question, but MIT neuroscientists have now answered that question for one commonly used anesthesia drug.

Using a novel technique for analyzing neuron activity, the researchers discovered that the drug propofol induces unconsciousness by disrupting the brain’s normal balance between stability and excitability. The drug causes brain activity to become increasingly unstable, until the brain loses consciousness.

“The brain has to operate on this knife’s edge between excitability and chaos. It’s got to be excitable enough for its neurons to influence one another, but if it gets too excitable, it spins off into chaos. Propofol seems to disrupt the mechanisms that keep the brain in that narrow operating range,” says Earl K. Miller, the Picower Professor of Neuroscience and a member of MIT’s Picower Institute for Learning and Memory.

The new findings, reported today in Neuron , could help researchers develop better tools for monitoring patients as they undergo general anesthesia.

Miller and Ila Fiete, a professor of brain and cognitive sciences, the director of the K. Lisa Yang Integrative Computational Neuroscience Center (ICoN), and a member of MIT’s McGovern Institute for Brain Research, are the senior authors of the new study. MIT graduate student Adam Eisen and MIT postdoc Leo Kozachkov are the lead authors of the paper.

Losing consciousness

Propofol is a drug that binds to GABA receptors in the brain, inhibiting neurons that have those receptors. Other anesthesia drugs act on different types of receptors, and the mechanism for how all of these drugs produce unconsciousness is not fully understood.

Miller, Fiete, and their students hypothesized that propofol, and possibly other anesthesia drugs, interfere with a brain state known as “dynamic stability.” In this state, neurons have enough excitability to respond to new input, but the brain is able to quickly regain control and prevent them from becoming overly excited.

Previous studies of how anesthesia drugs affect this balance have found conflicting results: Some suggested that during anesthesia, the brain shifts toward becoming too stable and unresponsive, which leads to loss of consciousness. Others found that the brain becomes too excitable, leading to a chaotic state that results in unconsciousness.

Part of the reason for these conflicting results is that it has been difficult to accurately measure dynamic stability in the brain. Measuring dynamic stability as consciousness is lost would help researchers determine if unconsciousness results from too much stability or too little stability.

In this study, the researchers analyzed electrical recordings made in the brains of animals that received propofol over an hour-long period, during which they gradually lost consciousness. The recordings were made in four areas of the brain that are involved in vision, sound processing, spatial awareness, and executive function.

These recordings covered only a tiny fraction of the brain’s overall activity, so to overcome that, the researchers used a technique called delay embedding. This technique allows researchers to characterize dynamical systems from limited measurements by augmenting each measurement with measurements that were recorded previously.

Using this method, the researchers were able to quantify how the brain responds to sensory inputs, such as sounds, or to spontaneous perturbations of neural activity.

In the normal, awake state, neural activity spikes after any input, then returns to its baseline activity level. However, once propofol dosing began, the brain started taking longer to return to its baseline after these inputs, remaining in an overly excited state. This effect became more and more pronounced until the animals lost consciousness.

This suggests that propofol’s inhibition of neuron activity leads to escalating instability, which causes the brain to lose consciousness, the researchers say.

Better anesthesia control

To see if they could replicate this effect in a computational model, the researchers created a simple neural network. When they increased the inhibition of certain nodes in the network, as propofol does in the brain, network activity became destabilized, similar to the unstable activity the researchers saw in the brains of animals that received propofol.

“We looked at a simple circuit model of interconnected neurons, and when we turned up inhibition in that, we saw a destabilization. So, one of the things we’re suggesting is that an increase in inhibition can generate instability, and that is subsequently tied to loss of consciousness,” Eisen says.

As Fiete explains, “This paradoxical effect, in which boosting inhibition destabilizes the network rather than silencing or stabilizing it, occurs because of disinhibition. When propofol boosts the inhibitory drive, this drive inhibits other inhibitory neurons, and the result is an overall increase in brain activity.”

The researchers suspect that other anesthetic drugs, which act on different types of neurons and receptors, may converge on the same effect through different mechanisms — a possibility that they are now exploring.

If this turns out to be true, it could be helpful to the researchers’ ongoing efforts to develop ways to more precisely control the level of anesthesia that a patient is experiencing. These systems, which Miller is working on with Emery Brown, the Edward Hood Taplin Professor of Medical Engineering at MIT, work by measuring the brain’s dynamics and then adjusting drug dosages accordingly, in real-time.

“If you find common mechanisms at work across different anesthetics, you can make them all safer by tweaking a few knobs, instead of having to develop safety protocols for all the different anesthetics one at a time,” Miller says. “You don’t want a different system for every anesthetic they’re going to use in the operating room. You want one that’ll do it all.”

The researchers also plan to apply their technique for measuring dynamic stability to other brain states, including neuropsychiatric disorders.

“This method is pretty powerful, and I think it’s going to be very exciting to apply it to different brain states, different types of anesthetics, and also other neuropsychiatric conditions like depression and schizophrenia,” Fiete says.

The research was funded by the Office of Naval Research, the National Institute of Mental Health, the National Institute of Neurological Disorders and Stroke, the National Science Foundation Directorate for Computer and Information Science and Engineering, the Simons Center for the Social Brain, the Simons Collaboration on the Global Brain, the JPB Foundation, the McGovern Institute, and the Picower Institute. 

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MIT scientists have discovered how propofol, a commonly used anesthetic, induces unconsciousness, reports Adam Kovac for Gizmodo . “The new research indicates that [propofol] works by interfering with a brain’s ‘dynamic stability’ – a state where neurons can respond to input, but the brain is able to keep them from getting too excited,” explains Kovac. 

IFL Science

MIT researchers have discovered how propofol, a commonly used anesthetic, works on the brain, reports Francesca Benson for IFL Science . The research studied “the differences between an awake brain and one under anesthesia by looking at the stability of the brain’s activity,” writes Bensen. 

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How Kamala Harris fares against Trump in the 2024 polls

With President Joe Biden exiting the 2024 presidential race, Vice President Kamala Harris now becomes the overwhelming front-runner to be the Democratic Party’s presidential nominee.

Harris’ biggest challenge lies further ahead, though: She   has been polling   the same as Biden — or just slightly better — against Republican nominee Donald Trump, according to multiple surveys taken before Biden withdrew from the 2024 contest.

And Biden was running behind Trump in many national and battleground-state polls — which precipitated the president’s withdrawal.

In  NBC News’ latest national poll , conducted more than a week after Biden’s dismal debate performance but before the assassination attempt on Trump, both the president and Harris trailed Trump by 2-point margins among registered voters, though the actual percentages for each candidate were slightly different. Trump led Biden 45%-43%, while he took 47% to Harris’ 45% in their matchup. Both ballot tests fell within the poll’s margin of error.

Similarly, a post-debate  national Fox News poll  found Trump ahead by 1 point against both Biden (Trump 49%, Biden 48%) and Harris (Trump 49%, Harris 48%) among registered voters.

But other polls have shown Harris slightly outperforming Biden by 1 or 2 points — though, critically, still trailing Trump at this point in some key matchups.

A  national CBS News/YouGov poll  of likely voters conducted after the assassination attempt found Trump leading Biden by 5 points among likely voters, 52% to 47%, while it showed Harris trailing by 3 points, 51% to 48%.

And in  New York Times/Siena College battleground polls  of Pennsylvania and Virginia, Harris performed 2 points better than Biden did among likely voters in these two states.

Importantly, all of these results are within each poll’s margin of error — and so is the difference between Biden’s and Harris’ numbers. Also important: It’s possible these numbers could change after the news of Biden’s exit from the 2024 race. But for the moment, Biden’s numbers and Harris’ numbers look quite similar.

Where Harris runs stronger — and weaker — than Biden

While the recent NBC News poll found Biden and Harris running 2 points behind Trump nationally, the survey found some  important differences among demographic groups .

For one thing, Harris slightly outperformed Biden among Black voters, leading Trump among this demographic by 64 points (78% to 14%). That compares with Biden’s 57-point lead among Black voters (69%-12%).

 On the other hand, the NBC News poll showed Trump doing slightly better among white voters when matched up with Harris instead of Biden, leading her by 16 points among these voters, compared with his 14-point advantage here against Biden.

Among other demographics — by age, by gender, among Latino voters — there was almost no difference between Biden or Harris.

Indeed, the biggest differences between Biden and Harris in the poll went well beyond demographics.

Among the roughly one-quarter of Republican registered voters in the poll who said they were unsatisfied with Trump as the GOP’s nominee, Trump ran ahead of Biden by 46 points, 63%-17%. But when Trump’s opponent was Harris, more of these dissatisfied GOP voters flocked to Trump. The Republican’s lead with that group grew to 57 points, 73%-16%.

Meanwhile, the voters who preferred a third-party candidate in the poll’s multicandidate ballot test seemed more open to Harris coming in as a fresh face in the 2024 race.

Trump and Biden were virtually tied with these third-party-interested   voters in a head-to-head matchup. Trump took   32% and   Biden took   31%, with a plurality declining to make a two-way choice, saying they were undecided, would pick another candidate, or something else.

But when Harris was the choice against Trump, more of those respondents made a pick in the two-way ballot test. The vice president went ahead of Trump among these “other” voters, 46% to 39%, suggesting a higher upside with voters currently   considering a third-party candidate.

Biden, Harris and Trump have almost equal positive-negative scores

The NBC News poll also  showed  Biden, Harris and Trump with almost equal positive-negative scores with the electorate.

• Trump: 38% positive, 53% negative (-15 net rating)
• Biden: 36% positive, 53% negative (-17 net rating)
• Harris: 32% positive, 50% negative (-18 net rating)

That said, while Harris had a slightly lower positive score in the poll, 15% of voters said they’re “neutral” about her, compared with just 11% who are neutral on Biden.

That suggests an opportunity for Harris to grow — or fall — with this sliver of voters in the middle.

Mark Murray is a senior political editor at NBC News.

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