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Posts Tagged ‘science communication’

ChatGPT Searches and Advent of Meta Threads: What it Means for Social Media and Science 3.0

Curator: Stephen J. Williams, PhD

The following explains how popular ChatGPT has become and how the latest social media platforms, including Meta’s (FaceBook) new platform Threads, is becoming as popular or more popular than older social Platforms.  In fact, since its short inception since last week (Threads launced 7/07/2023), Threads is threatening Twitter for dominance in that market.

The following is taken from an email from Charlie Downing Jones from journoreasearch.org and  https://www.digital-adoption.com/ :

U.S. searches for ChatGPT overtake TikTok, Pinterest, and Zoom

  • Google searches for ChatGPT have overtaken TikTok in the U.S., jumping to 7.1 million monthly searches compared to 5.1 million
  • The term ‘ChatGPT’ is now one of the top 100 search terms in the U.S., ranking 92nd, according to Ahrefs data
  • ChatGPT is now searched more than most major social networks, including LinkedIn, Pinterest, TikTok, and Reddit

Analysis of Google search data reveals that online searches for ChatGPT, the popular AI chatbot, have overtaken most popular social networks in the U.S. This comes when search interest in artificial intelligence is at its highest point in history.

 

The findings by Digital-adoption.com reveal that US-based searches for ChatGPT have exploded and overtaken popular social networks, such as LinkedIn, Pinterest, and Tiktok, some by millions.

 

Ranking Keyword US Search Volume (Monthly)
1 Facebook                                  70,920,000
2 YouTube                                  69,260,000
3 Twitter                                  15,440,000
4 Instagram                                  12,240,000
5 ChatGPT                                  7,130,000
6 LinkedIn                                  6,990,000
7 Pinterest                                  5,790,000
8 TikTok                                  5,130,000
9 Reddit                                  4,060,000
10 Snapchat                                  1,280,000
11 WhatsApp                                  936,000

 

Since its release in November 2022, searches for ChatGPT have overtaken those of most major social networks. According to the latest June search figures by search tool Ahrefs, searches for ‘ChatGPT’ and ‘Chat GPT’ are made 7,130,000 times monthly in the U.S.

That’s more than the monthly search volume for most of the top ten social networks, including LinkedIn, Pinterest, and TikTok. TikTok is one of the largest growing social media apps, with 100 million users in just a year.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

The term ‘ChatGPT’ is now one of the top 100 search terms in the U.S., ranking 92nd, according to Ahrefs data

 

Searches for ChatGPT have eclipsed other major networks in the U.S., such as Reddit, by millions.

Every day search terms such as ‘maps’ and ‘flights’ have even seen their search volumes pale compared to the rising popularity of ChatGPT. ‘Maps’ is currently searched 440,000 times less than the chatbot each month, and ‘Flights’ is now Googled 2.2 million times less.

2023 has been a breakout year for AI, as searches for the term have more than doubled from 17 million in January 2023 to 42 million in May. In comparison, there were 7.9 million searches in January 2022. There has been an 825% increase in searches for ‘AI’ in the US compared to the average over the last five years.

There is a correlation between the uptick and the public releases of accessible AI chatbots such as ChatGPT, released on November 30, 2022, and Bing AI and Google Bard, released in May 2023.

According to TikTok data, interest in artificial intelligence has soared tenfold since 2020, and virtual reality has more than tripled.

AI has been a big topic of conversation this year as accessible AI chatbots and new technologies were released and sparked rapid adoption, prompting tech leaders like Elon Musk to call for AI regulation.

A spokesperson from Digital-adoption.com commented on the findings: “There has been a massive surge in AI interest this year. Apple’s announcement of Vision Pro has captured audiences at the right time, when new AI technologies, like ChatGPT, have become accessible to almost anyone. The rapid adoption of ChatGPT is surprising, with it becoming one of the fastest-growing tools available”.

All data was gathered from Ahrefs and Google Trends.

If using this story, please include a link to https://www.digital-adoption.com/ who conducted this study. A linked credit allows us to keep supplying you with content that you may find useful in the future.

 

If you need anything else, please get in touch.

All the best,
Charlie Dowling-Jones

 

charlie.dowling-jones@journoresearch.org

 

Journo Research

Part of Search Intelligence Ltd. Company registered in England No. 09361526

Why LPBI Needs to consider the new Meta Threads Platform

From Barrons

Threads Hits 100 Million Users Faster Than ChatGPT. Now It Needs Them to Stay.

 

By

Adam ClarkFollow

Updated July 10, 2023 9:00 am ET / Original July 10, 2023 7:44 am ET

The launch of Meta Platforms’ Threads looks to have outpaced even the viral success of ChatGPT in terms of signing up users. The next challenge will be keeping them around.

Since its inception on Thursday 7/07/2023, Meta’s new Threads platform has been signing up new users at an alarming rate.  On rollout date 5 million signed up, then 30 million by next morning and now as of today (7/1/2023) Threads has over 100 million signups.  Compare that to Twitter’s 436 million users, of which are tweeting on average 25% less than a few years ago, and it is easy to see why many social media pundits are calling Threads the new Twitter killer app.

 

Here are a few notes from the New York Times podcast The Daily

The Daily

1 day ago

Will Threads Kill Twitter?

Play • 33 min

Last week, Meta, the parent company of Facebook and Instagram, released Threads, a social media platform to compete with Twitter. In just 16 hours, Threads was downloaded more than 30 million times.

Mike Isaac, who covers tech companies and Silicon Valley for The Times, explains how Twitter became so vulnerable and discusses the challenges Meta faces to create a less toxic alternative.

Guest: Mike Isaac, a technology correspondent for The New York Times.

Background reading:

Here are a few notes from the podcast:

Mike Isaac lamented that Twitter has become user unfriendly for a host of reasons.  These include:

  • The instant reply’guys’ – people who reply but don’t really follow you or your thread
  • Your followers or following are not pushed to top of thread
  • The auto bots – the automated Twitter bots
  • Spam feeds
  • The changes in service and all these new fees: Twitter push to monetize everything – like airlines

Elon Musk wanted to transform Twitter but his history is always cutting, not just trimming the excess but he is known to just eliminate departments just because he either doesn’t want to pay or CAN’T pay.  With Twitter he gutted content moderation.

 

Twitter ad business is plumetting but Musk wants to make Twitter a subscription business (the Blue check mark)

Twitter only gets a couple of million $ per month from Twitter Blue but Musk has to pay billions to just pay the interest on Twitter loan for Twitter puchase years ago

It is known that Musk is not paying rent on some California offices (some are suggesting he defaulted on leases) and Musk is selling Tesla stock to pay for Twitter expenses (why TSLA stock has been falling … the consensus out there)

Twitter is largest compendium of natural language conversations and Musk wanted to limit bots from scraping Twitter data to do AI and NLP on Twitter threads.  This is also a grievance from other companies… that these ‘scrapers’ are not paying enough for Twitter data.  However as Mike asks why do the little Twitter user have to pay in either fees or cutbacks from service.  (the reason why Elon is limiting viewing per day is to limit these bots from scraping Twitter for data)

Another problem is that Twitter does not have its own servers so pays a lot to Google and AWS for server space.  It appears Elon and Twitter are running out of money.

META and THREADS

Zuckerberg has spent billions of infrastructure spending and created a massive advertising ecosystem.  This is one of the thoughts behind his push and entry into this space.  Zuckerberg actually wanted to but Twitter a decade ago.

 

Usage and growth:  The launch of Threads was Thursday 7-07-23. There were 2 million initial signups and by next morning 30 million overnight.  Today Monday 7-10-23 there are 100 million, rivaling Twitter’s 436 million accounts.  And as Musk keeps canceling Twitter accounts, angering users over fees or usage restrictions, people are looking for a good platform.  Mastedon in too technical and not having the adoption like Meta Threads is having.  Mike Isaac hopes Threads will not go the way of Google Hangouts or Plus but Google strategy did not involve social media like Facebook.

Signup and issues: Signup on Threads is easy but you need to go through Instagram.  Some people have concerns about having their instagram thread put on their Threads feed but Mike had talked to the people at Meta and they are working to allow users to keep the feeds separate, mainly because Meta understands that the Instgagram and Twitter social cultures are different and users may want to keep Threads more business-like.

Important issues for LPBI: Twitter had decided, by end of May 2023 to end their relationship with WordPress JetPack service, in which WordPress posts could automatically be posted to your Twitter account and feed.  Twitter is making users like WordPress pay for this API and WordPress said it would be too expensive as Twitter is not making a flat fee but per usage fee.  This is a major hindrance even though the Twitter social share button is still active on posts.

Initial conversations between META and WordPress have indicated META will keep this API service free for WordPress.

 

So a little background on Meta Threads and signup features from Meta (Facebook) website:

Takeaways

  • Threads is a new app, built by the Instagram team, for sharing text updates and joining public conversations.
  • You log in using your Instagram account and posts can be up to 500 characters long and include links, photos, and videos up to 5 minutes in length.
  • We’re working to soon make Threads compatible with the open, interoperable social networks that we believe can shape the future of the internet.

Mark Zuckerberg just announced the initial version of Threads, an app built by the Instagram team for sharing with text. Whether you’re a creator or a casual poster, Threads offers a new, separate space for real-time updates and public conversations. We are working toward making  Threads compatible with the open, interoperable social networks that we believe can shape the future of the internet.

Instagram is where billions of people around the world connect over photos and videos. Our vision with Threads is to take what Instagram does best and expand that to text, creating a positive and creative space to express your ideas. Just like on Instagram, with Threads you can follow and connect with friends and creators who share your interests – including the people you follow on Instagram and beyond. And you can use our existing suite of safety and user controls.

Join the Conversation from Instagram

It’s easy to get started with Threads: simply use your Instagram account to log in. Your Instagram username and verification will carry over, with the option to customize your profile specifically for Threads.

Everyone who is under 16 (or under 18 in certain countries) will be defaulted into a private profile when they join Threads. You can choose to follow the same accounts you do on Instagram, and find more people who care about the same things you do. The core accessibility features available on Instagram today, such as screen reader support and AI-generated image descriptions, are also enabled on Threads.

Your feed on Threads includes threads posted by people you follow, and recommended content from new creators you haven’t discovered yet. Posts can be up to 500 characters long and include links, photos, and videos up to 5 minutes in length. You can easily share a Threads post to your Instagram story, or share your post as a link on any other platform you choose.

Tune Out the Noise

We built Threads with tools to enable positive, productive conversations. You can control who can mention you or reply to you within Threads. Like on Instagram, you can add hidden words to filter out replies to your threads that contain specific words. You can unfollow, block, restrict or report a profile on Threads by tapping the three-dot menu, and any accounts you’ve blocked on Instagram will automatically be blocked on Threads.

As with all our products, we’re taking safety seriously, and we’ll enforce Instagram’s Community Guidelines on content and interactions in the app. Since 2016 we’ve invested more than $16 billion in building up the teams and technologies needed to protect our users, and we remain focused on advancing our industry-leading integrity efforts and investments to protect our community.

Compatible with Interoperable Networks

Soon, we are planning to make Threads compatible with ActivityPub, the open social networking protocol established by the World Wide Web Consortium (W3C), the body responsible for the open standards that power the modern web. This would make Threads interoperable with other apps that also support the ActivityPub protocol, such as Mastodon and WordPress – allowing new types of connections that are simply not possible on most social apps today. Other platforms including Tumblr have shared plans to support the ActivityPub protocol in the future.

We’re committed to giving you more control over your audience on Threads – our plan is to work  with ActivityPub to provide you the option to stop using Threads and transfer your content to another service. Our vision is that people using compatible apps will be able to follow and interact with people on Threads without having a Threads account, and vice versa, ushering in a new era of diverse and interconnected networks. If you have a public profile on Threads, this means your posts would be accessible from other apps, allowing you to reach new people with no added effort. If you have a private profile, you’d be able to approve users on Threads who want to follow you and interact with your content, similar to your experience on Instagram.

The benefits of open social networking protocols go well beyond the ways people can follow each other. Developers can build new types of features and user experiences that can easily plug into other open social networks, accelerating the pace of innovation and experimentation. Each compatible app can set its own community standards and content moderation policies, meaning people have the freedom to choose spaces that align with their values. We believe this decentralized approach, similar to the protocols governing email and the web itself, will play an important role in the future of online platforms.

Threads is Meta’s first app envisioned to be compatible with an open social networking protocol – we hope that by joining this fast-growing ecosystem of interoperable services, Threads will help people find their community, no matter what app they use.

What’s Next

We’re rolling out Threads today in more than 100 countries for iOS and Android, and people in those countries can download the app from the Apple App Store and Google Play Store.

In addition to working toward making Threads compatible with the ActivityPub protocol, soon we’ll be adding a number of new features to help you continue to discover threads and creators you’re interested in, including improved recommendations in feed and a more robust search function that makes it easier to follow topics and trends in real time.

 

Should Science Migrate over to Threads Instead of Twitter?

I have written multiple time of the impact of social media, Science and Web 2.0 and the new Science and Web 3.0 including

Will Web 3.0 Do Away With Science 2.0? Is Science Falling Behind?

Science Has A Systemic Problem, Not an Innovation Problem

 

It, as of this writing, appears it is not crucial that scientific institutions need to migrate over to Threads yet, although the impetus is certainly there.  Many of the signups have of course been through Instagram (which is the only way to signup for now) and a search of @Threads does not show that large scientific organizations have signed up for now.

 

A search for NIH, NCBI, AACR, and Personalized Medicine Coalition or PMC which is the big MGH orgaization on personalized medicine appears to return nothing yet.  Pfizer and most big pharma is on @Threads now but that is because they maintain a marketing thread on Instagram.  How necessary is @Threads for communicating science over Science 3.0 platform remains to be seen.  In addition, how will @Threads be used for real time scientific conference coverage?  Will Meta be able to integrate with virtual reality?

Other articles of Note on this Open Access Scientific Journal Include:

Will Web 3.0 Do Away With Science 2.0? Is Science Falling Behind?

Science Has A Systemic Problem, Not an Innovation Problem

Relevance of Twitter.com forthcoming Payment System for Scientific Content Promotion and Monetization

Is It Time for the Virtual Scientific Conference?: Coronavirus, Travel Restrictions, Conferences Cancelled

Part One: The Process of Real Time Coverage using Social Media

 

 

 

 

 

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Will Web 3.0 Do Away With Science 2.0? Is Science Falling Behind?

Curator: Stephen J. Williams, Ph.D.

UPDATED 4/06/2022

A while back (actually many moons ago) I had put on two posts on this site:

Scientific Curation Fostering Expert Networks and Open Innovation: Lessons from Clive Thompson and others

Twitter is Becoming a Powerful Tool in Science and Medicine

Each of these posts were on the importance of scientific curation of findings within the realm of social media and the Web 2.0; a sub-environment known throughout the scientific communities as Science 2.0, in which expert networks collaborated together to produce massive new corpus of knowledge by sharing their views, insights on peer reviewed scientific findings. And through this new media, this process of curation would, in itself generate new ideas and new directions for research and discovery.

The platform sort of looked like the image below:

 

This system lied above a platform of the original Science 1.0, made up of all the scientific journals, books, and traditional literature:

In the old Science 1.0 format, scientific dissemination was in the format of hard print journals, and library subscriptions were mandatory (and eventually expensive). Open Access has tried to ameliorate the expense problem.

Previous image source: PeerJ.com

To index the massive and voluminous research and papers beyond the old Dewey Decimal system, a process of curation was mandatory. The dissemination of this was a natural for the new social media however the cost had to be spread out among numerous players. Journals, faced with the high costs of subscriptions and their only way to access this new media as an outlet was to become Open Access, a movement first sparked by journals like PLOS and PeerJ but then begrudingly adopted throughout the landscape. But with any movement or new adoption one gets the Good the Bad and the Ugly (as described in my cited, above, Clive Thompson article). The bad side of Open Access Journals were

  1. costs are still assumed by the individual researcher not by the journals
  2. the arise of the numerous Predatory Journals

 

Even PeerJ, in their column celebrating an anniversary of a year’s worth of Open Access success stories, lamented the key issues still facing Open Access in practice

  • which included the cost and the rise of predatory journals.

In essence, Open Access and Science 2.0 sprung full force BEFORE anyone thought of a way to defray the costs

 

Can Web 3.0 Finally Offer a Way to Right the Issues Facing High Costs of Scientific Publishing?

What is Web 3.0?

From Wikipedia: https://en.wikipedia.org/wiki/Web3

Web 1.0 and Web 2.0 refer to eras in the history of the Internet as it evolved through various technologies and formats. Web 1.0 refers roughly to the period from 1991 to 2004, where most websites were static webpages, and the vast majority of users were consumers, not producers, of content.[6][7] Web 2.0 is based around the idea of “the web as platform”,[8] and centers on user-created content uploaded to social-networking services, blogs, and wikis, among other services.[9] Web 2.0 is generally considered to have begun around 2004, and continues to the current day.[8][10][4]

Terminology[edit]

The term “Web3”, specifically “Web 3.0”, was coined by Ethereum co-founder Gavin Wood in 2014.[1] In 2020 and 2021, the idea of Web3 gained popularity[citation needed]. Particular interest spiked towards the end of 2021, largely due to interest from cryptocurrency enthusiasts and investments from high-profile technologists and companies.[4][5] Executives from venture capital firm Andreessen Horowitz travelled to Washington, D.C. in October 2021 to lobby for the idea as a potential solution to questions about Internet regulation with which policymakers have been grappling.[11]

Web3 is distinct from Tim Berners-Lee‘s 1999 concept for a semantic web, which has also been called “Web 3.0”.[12] Some writers referring to the decentralized concept usually known as “Web3” have used the terminology “Web 3.0”, leading to some confusion between the two concepts.[2][3] Furthermore, some visions of Web3 also incorporate ideas relating to the semantic web.[13][14]

Concept[edit]

Web3 revolves around the idea of decentralization, which proponents often contrast with Web 2.0, wherein large amounts of the web’s data and content are centralized in the fairly small group of companies often referred to as Big Tech.[4]

Specific visions for Web3 differ, but all are heavily based in blockchain technologies, such as various cryptocurrencies and non-fungible tokens (NFTs).[4] Bloomberg described Web3 as an idea that “would build financial assets, in the form of tokens, into the inner workings of almost anything you do online”.[15] Some visions are based around the concepts of decentralized autonomous organizations (DAOs).[16] Decentralized finance (DeFi) is another key concept; in it, users exchange currency without bank or government involvement.[4] Self-sovereign identity allows users to identify themselves without relying on an authentication system such as OAuth, in which a trusted party has to be reached in order to assess identity.[17]

Reception[edit]

Technologists and journalists have described Web3 as a possible solution to concerns about the over-centralization of the web in a few “Big Tech” companies.[4][11] Some have expressed the notion that Web3 could improve data securityscalability, and privacy beyond what is currently possible with Web 2.0 platforms.[14] Bloomberg states that sceptics say the idea “is a long way from proving its use beyond niche applications, many of them tools aimed at crypto traders”.[15] The New York Times reported that several investors are betting $27 billion that Web3 “is the future of the internet”.[18][19]

Some companies, including Reddit and Discord, have explored incorporating Web3 technologies into their platforms in late 2021.[4][20] After heavy user backlash, Discord later announced they had no plans to integrate such technologies.[21] The company’s CEO, Jason Citron, tweeted a screenshot suggesting it might be exploring integrating Web3 into their platform. This led some to cancel their paid subscriptions over their distaste for NFTs, and others expressed concerns that such a change might increase the amount of scams and spam they had already experienced on crypto-related Discord servers.[20] Two days later, Citron tweeted that the company had no plans to integrate Web3 technologies into their platform, and said that it was an internal-only concept that had been developed in a company-wide hackathon.[21]

Some legal scholars quoted by The Conversation have expressed concerns over the difficulty of regulating a decentralized web, which they reported might make it more difficult to prevent cybercrimeonline harassmenthate speech, and the dissemination of child abuse images.[13] But, the news website also states that, “[decentralized web] represents the cyber-libertarian views and hopes of the past that the internet can empower ordinary people by breaking down existing power structures.” Some other critics of Web3 see the concept as a part of a cryptocurrency bubble, or as an extension of blockchain-based trends that they see as overhyped or harmful, particularly NFTs.[20] Some critics have raised concerns about the environmental impact of cryptocurrencies and NFTs. Others have expressed beliefs that Web3 and the associated technologies are a pyramid scheme.[5]

Kevin Werbach, author of The Blockchain and the New Architecture of Trust,[22] said that “many so-called ‘web3’ solutions are not as decentralized as they seem, while others have yet to show they are scalable, secure and accessible enough for the mass market”, adding that this “may change, but it’s not a given that all these limitations will be overcome”.[23]

David Gerard, author of Attack of the 50 Foot Blockchain,[24] told The Register that “web3 is a marketing buzzword with no technical meaning. It’s a melange of cryptocurrencies, smart contracts with nigh-magical abilities, and NFTs just because they think they can sell some monkeys to morons”.[25]

Below is an article from MarketWatch.com Distributed Ledger series about the different forms and cryptocurrencies involved

From Marketwatch: https://www.marketwatch.com/story/bitcoin-is-so-2021-heres-why-some-institutions-are-set-to-bypass-the-no-1-crypto-and-invest-in-ethereum-other-blockchains-next-year-11639690654?mod=home-page

by Frances Yue, Editor of Distributed Ledger, Marketwatch.com

Clayton Gardner, co-CEO of crypto investment management firm Titan, told Distributed Ledger that as crypto embraces broader adoption, he expects more institutions to bypass bitcoin and invest in other blockchains, such as Ethereum, Avalanche, and Terra in 2022. which all boast smart-contract features.

Bitcoin traditionally did not support complex smart contracts, which are computer programs stored on blockchains, though a major upgrade in November might have unlocked more potential.

“Bitcoin was originally seen as a macro speculative asset by many funds and for many it still is,” Gardner said. “If anything solidifies its use case, it’s a store of value. It’s not really used as originally intended, perhaps from a medium of exchange perspective.”

For institutions that are looking for blockchains that can “produce utility and some intrinsic value over time,” they might consider some other smart contract blockchains that have been driving the growth of decentralized finance and web 3.0, the third generation of the Internet, according to Gardner. 

Bitcoin is still one of the most secure blockchains, but I think layer-one, layer-two blockchains beyond Bitcoin, will handle the majority of transactions and activities from NFT (nonfungible tokens) to DeFi,“ Gardner said. “So I think institutions see that and insofar as they want to put capital to work in the coming months, I think that could be where they just pump the capital.”

Decentralized social media? 

The price of Decentralized Social, or DeSo, a cryptocurrency powering a blockchain that supports decentralized social media applications, surged roughly 74% to about $164 from $94, after Deso was listed at Coinbase Pro on Monday, before it fell to about $95, according to CoinGecko.

In the eyes of Nader Al-Naji, head of the DeSo foundation, decentralized social media has the potential to be “a lot bigger” than decentralized finance.

“Today there are only a few companies that control most of what we see online,” Al-Naji told Distributed Ledger in an interview. But DeSo is “creating a lot of new ways for creators to make money,” Al-Naji said.

“If you find a creator when they’re small, or an influencer, you can invest in that, and then if they become bigger and more popular, you make money and they make and they get capital early on to produce their creative work,” according to AI-Naji.

BitClout, the first application that was created by AI-Naji and his team on the DeSo blockchain, had initially drawn controversy, as some found that they had profiles on the platform without their consent, while the application’s users were buying and selling tokens representing their identities. Such tokens are called “creator coins.”

AI-Naji responded to the controversy saying that DeSo now supports more than 200 social-media applications including Bitclout. “I think that if you don’t like those features, you now have the freedom to use any app you want. Some apps don’t have that functionality at all.”

 

But Before I get to the “selling monkeys to morons” quote,

I want to talk about

THE GOOD, THE BAD, AND THE UGLY

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

THE GOOD

My foray into Science 2.0 and then pondering what the movement into a Science 3.0 led me to an article by Dr. Vladimir Teif, who studies gene regulation and the nucleosome, as well as creating a worldwide group of scientists who discuss matters on chromatin and gene regulation in a journal club type format.

For more information on this Fragile Nucleosome journal club see https://generegulation.org/fragile-nucleosome/.

Fragile Nucleosome is an international community of scientists interested in chromatin and gene regulation. Fragile Nucleosome is active in several spaces: one is the Discord server where several hundred scientists chat informally on scientific matters. You can join the Fragile Nucleosome Discord server. Another activity of the group is the organization of weekly virtual seminars on Zoom. Our webinars are usually conducted on Wednesdays 9am Pacific time (5pm UK, 6pm Central Europe). Most previous seminars have been recorded and can be viewed at our YouTube channel. The schedule of upcoming webinars is shown below. Our third activity is the organization of weekly journal clubs detailed at a separate page (Fragile Nucleosome Journal Club).

 

His lab site is at https://generegulation.org/ but had published a paper describing what he felt what the #science2_0 to #science3_0 transition would look like (see his blog page on this at https://generegulation.org/open-science/).

This concept of science 3.0 he had coined back in 2009.  As Dr Teif had mentioned

So essentially I first introduced this word Science 3.0 in 2009, and since then we did a lot to implement this in practice. The Twitter account @generegulation is also one of examples

 

This is curious as we still have an ill defined concept of what #science3_0 would look like but it is a good read nonetheless.

His paper,  entitled “Science 3.0: Corrections to the Science 2.0 paradigm” is on the Cornell preprint server at https://arxiv.org/abs/1301.2522 

 

Abstract

Science 3.0: Corrections to the Science 2.0 paradigm

The concept of Science 2.0 was introduced almost a decade ago to describe the new generation of online-based tools for researchers allowing easier data sharing, collaboration and publishing. Although technically sound, the concept still does not work as expected. Here we provide a systematic line of arguments to modify the concept of Science 2.0, making it more consistent with the spirit and traditions of science and Internet. Our first correction to the Science 2.0 paradigm concerns the open-access publication models charging fees to the authors. As discussed elsewhere, we show that the monopoly of such publishing models increases biases and inequalities in the representation of scientific ideas based on the author’s income. Our second correction concerns post-publication comments online, which are all essentially non-anonymous in the current Science 2.0 paradigm. We conclude that scientific post-publication discussions require special anonymization systems. We further analyze the reasons of the failure of the current post-publication peer-review models and suggest what needs to be changed in Science 3.0 to convert Internet into a large journal club. [bold face added]
In this paper it is important to note the transition of a science 1.0, which involved hard copy journal publications usually only accessible in libraries to a more digital 2.0 format where data, papers, and ideas could be easily shared among networks of scientists.
As Dr. Teif states, the term “Science 2.0” had been coined back in 2009, and several influential journals including Science, Nature and Scientific American endorsed this term and suggested scientists to move online and their discussions online.  However, even at present there are thousands on this science 2.0 platform, Dr Teif notes the number of scientists subscribed to many Science 2.0 networking groups such as on LinkedIn and ResearchGate have seemingly saturated over the years, with little new members in recent times. 
The consensus is that science 2.0 networking is:
  1. good because it multiplies the efforts of many scientists, including experts and adds to the scientific discourse unavailable on a 1.0 format
  2. that online data sharing is good because it assists in the process of discovery (can see this evident with preprint servers, bio-curated databases, Github projects)
  3. open-access publishing is beneficial because free access to professional articles and open-access will be the only publishing format in the future (although this is highly debatable as many journals are holding on to a type of “hybrid open access format” which is not truly open access
  4. only sharing of unfinished works and critiques or opinions is good because it creates visibility for scientists where they can receive credit for their expert commentary

There are a few concerns on Science 3.0 Dr. Teif articulates:

A.  Science 3.0 Still Needs Peer Review

Peer review of scientific findings will always be an imperative in the dissemination of well-done, properly controlled scientific discovery.  As Science 2.0 relies on an army of scientific volunteers, the peer review process also involves an army of scientific experts who give their time to safeguard the credibility of science, by ensuring that findings are reliable and data is presented fairly and properly.  It has been very evident, in this time of pandemic and the rapid increase of volumes of preprint server papers on Sars-COV2, that peer review is critical.  Many of these papers on such preprint servers were later either retracted or failed a stringent peer review process.

Now many journals of the 1.0 format do not generally reward their peer reviewers other than the self credit that researchers use on their curriculum vitaes.  Some journals, like the MDPI journal family, do issues peer reviewer credits which can be used to defray the high publication costs of open access (one area that many scientists lament about the open access movement; where the burden of publication cost lies on the individual researcher).

An issue which is highlighted is the potential for INFORMATION NOISE regarding the ability to self publish on Science 2.0 platforms.

 

The NEW BREED was born in 4/2012

An ongoing effort on this platform, https://pharmaceuticalintelligence.com/, is to establish a scientific methodology for curating scientific findings where one the goals is to assist to quell the information noise that can result from the massive amounts of new informatics and data occurring in the biomedical literature. 

B.  Open Access Publishing Model leads to biases and inequalities in the idea selection

The open access publishing model has been compared to the model applied by the advertising industry years ago and publishers then considered the journal articles as “advertisements”.  However NOTHING could be further from the truth.  In advertising the publishers claim the companies not the consumer pays for the ads.  However in scientific open access publishing, although the consumer (libraries) do not pay for access the burden of BOTH the cost of doing the research and publishing the findings is now put on the individual researcher.  Some of these publishing costs can be as high as $4000 USD per article, which is very high for most researchers.  However many universities try to refund the publishers if they do open access publishing so it still costs the consumer and the individual researcher, limiting the cost savings to either.  

However, this sets up a situation in which young researchers, who in general are not well funded, are struggling with the publication costs, and this sets up a bias or inequitable system which rewards the well funded older researchers and bigger academic labs.

C. Post publication comments and discussion require online hubs and anonymization systems

Many recent publications stress the importance of a post-publication review process or system yet, although many big journals like Nature and Science have their own blogs and commentary systems, these are rarely used.  In fact they show that there are just 1 comment per 100 views of a journal article on these systems.  In the traditional journals editors are the referees of comments and have the ability to censure comments or discourse.  The article laments that comments should be easy to do on journals, like how easy it is to make comments on other social sites, however scientists are not offering their comments or opinions on the matter. 

In a personal experience, 

a well written commentary goes through editors which usually reject a comment like they were rejecting an original research article.  Thus many scientists, I believe, after fashioning a well researched and referenced reply, do not get the light of day if not in the editor’s interests.  

Therefore the need for anonymity is greatly needed and the lack of this may be the hindrance why scientific discourse is so limited on these types of Science 2.0 platforms.  Platforms that have success in this arena include anonymous platforms like Wikipedia or certain closed LinkedIn professional platforms but more open platforms like Google Knowledge has been a failure.

A great example on this platform was a very spirited conversation on LinkedIn on genomics, tumor heterogeneity and personalized medicine which we curated from the LinkedIn discussion (unfortunately LinkedIn has closed many groups) seen here:

Issues in Personalized Medicine: Discussions of Intratumor Heterogeneity from the Oncology Pharma forum on LinkedIn

 

 

Issues in Personalized Medicine: Discussions of Intratumor Heterogeneity from the Oncology Pharma forum on LinkedIn

 

In this discussion, it was surprising that over a weekend so many scientists from all over the world contributed to a great discussion on the topic of tumor heterogeneity.

But many feel such discussions would be safer if they were anonymized.  However then researchers do not get any credit for their opinions or commentaries.

A Major problem is how to take the intangible and make them into tangible assets which would both promote the discourse as well as reward those who take their time to improve scientific discussion.

This is where something like NFTs or a decentralized network may become important!

See

https://pharmaceuticalintelligence.com/portfolio-of-ip-assets/

 

UPDATED 5/09/2022

Below is an online @TwitterSpace Discussion we had with some young scientists who are just starting out and gave their thoughts on what SCIENCE 3.0 and the future of dissemination of science might look like, in light of this new Meta Verse.  However we have to define each of these terms in light of Science and not just the Internet as merely a decentralized marketplace for commonly held goods.

This online discussion was tweeted out and got a fair amount of impressions (60) as well as interactors (50).

 For the recording on both Twitter as well as on an audio format please see below

<blockquote class=”twitter-tweet”><p lang=”en” dir=”ltr”>Set a reminder for my upcoming Space! <a href=”https://t.co/7mOpScZfGN”>https://t.co/7mOpScZfGN</a&gt; <a href=”https://twitter.com/Pharma_BI?ref_src=twsrc%5Etfw”>@Pharma_BI</a&gt; <a href=”https://twitter.com/PSMTempleU?ref_src=twsrc%5Etfw”>@PSMTempleU</a&gt; <a href=”https://twitter.com/hashtag/science3_0?src=hash&amp;ref_src=twsrc%5Etfw”>#science3_0</a&gt; <a href=”https://twitter.com/science2_0?ref_src=twsrc%5Etfw”>@science2_0</a></p>&mdash; Stephen J Williams (@StephenJWillia2) <a href=”https://twitter.com/StephenJWillia2/status/1519776668176502792?ref_src=twsrc%5Etfw”>April 28, 2022</a></blockquote> <script async src=”https://platform.twitter.com/widgets.js&#8221; charset=”utf-8″></script>

 

 

To introduce this discussion first a few startoff material which will fram this discourse

 






The Intenet and the Web is rapidly adopting a new “Web 3.0” format, with decentralized networks, enhanced virtual experiences, and greater interconnection between people. Here we start the discussion what will the move from Science 2.0, where dissemination of scientific findings was revolutionized and piggybacking on Web 2.0 or social media, to a Science 3.0 format. And what will it involve or what paradigms will be turned upside down?

Old Science 1.0 is still the backbone of all scientific discourse, built on the massive amount of experimental and review literature. However this literature was in analog format, and we moved to a more accesible digital open access format for both publications as well as raw data. However as there was a structure for 1.0, like the Dewey decimal system and indexing, 2.0 made science more accesible and easier to search due to the newer digital formats. Yet both needed an organizing structure; for 1.0 that was the scientific method of data and literature organization with libraries as the indexers. In 2.0 this relied on an army mostly of volunteers who did not have much in the way of incentivization to co-curate and organize the findings and massive literature.

Each version of Science has their caveats: their benefits as well as deficiencies. This curation and the ongoing discussion is meant to solidy the basis for the new format, along with definitions and determination of structure.

We had high hopes for Science 2.0, in particular the smashing of data and knowledge silos. However the digital age along with 2.0 platforms seemed to excaccerbate this somehow. We still are critically short on analysis!

 

We really need people and organizations to get on top of this new Web 3.0 or metaverse so the similar issues do not get in the way: namely we need to create an organizing structure (maybe as knowledgebases), we need INCENTIVIZED co-curators, and we need ANALYSIS… lots of it!!

Are these new technologies the cure or is it just another headache?

 

There were a few overarching themes whether one was talking about AI, NLP, Virtual Reality, or other new technologies with respect to this new meta verse and a concensus of Decentralized, Incentivized, and Integrated was commonly expressed among the attendees

The Following are some slides from representative Presentations

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Other article of note on this topic on this Open Access Scientific Journal Include:

Electronic Scientific AGORA: Comment Exchanges by Global Scientists on Articles published in the Open Access Journal @pharmaceuticalintelligence.com – Four Case Studies

eScientific Publishing a Case in Point: Evolution of Platform Architecture Methodologies and of Intellectual Property Development (Content Creation by Curation) Business Model 

e-Scientific Publishing: The Competitive Advantage of a Powerhouse for Curation of Scientific Findings and Methodology Development for e-Scientific Publishing – LPBI Group, A Case in Point

@PharmaceuticalIntelligence.com –  A Case Study on the LEADER in Curation of Scientific Findings

Real Time Coverage @BIOConvention #BIO2019: Falling in Love with Science: Championing Science for Everyone, Everywhere

Old Industrial Revolution Paradigm of Education Needs to End: How Scientific Curation Can Transform Education

 

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Live Conference Coverage @Medcitynews Converge 2018 @Philadelphia: Promising Drugs and Breaking Down Silos

Reporter: Stephen J. Williams, PhD

Promising Drugs, Pricing and Access

The drug pricing debate rages on. What are the solutions to continuing to foster research and innovation, while ensuring access and affordability for patients? Can biosimilars and generics be able to expand market access in the U.S.?

Moderator: Bunny Ellerin, Director, Healthcare and Pharmaceutical Management Program, Columbia Business School
Speakers:
Patrick Davish, AVP, Global & US Pricing/Market Access, Merck
Robert Dubois M.D., Chief Science Officer and Executive Vice President, National Pharmaceutical Council
Gary Kurzman, M.D., Senior Vice President and Managing Director, Healthcare, Safeguard Scientifics
Steven Lucio, Associate Vice President, Pharmacy Services, Vizient

What is working and what needs to change in pricing models?

Robert:  He sees so many players in the onStevencology space discovering new drugs and other drugs are going generic (that is what is working).  However are we spending too much on cancer care relative to other diseases (their initiative Going Beyond the Surface)

Steven:  the advent of biosimilars is good for the industry

Patrick:  large effort in oncology, maybe too much (750 trials on Keytruda) and he says pharma is spending on R&D (however clinical trials take large chunk of this money)

Robert: cancer has gotten a free ride but cost per year relative to benefit looks different than other diseases.  Are we overinvesting in cancer or is that a societal decision

Gary:  maybe as we become more specific with precision medicines high prices may be a result of our success in specifically targeting a mutation.  We need to understand the targeted drugs and outcomes.

Patrick: “Cancer is the last big frontier” but he says prices will come down in most cases.  He gives the example of Hep C treatment… the previous only therapeutic option was a very toxic yearlong treatment but the newer drugs may be more cost effective and safer

Steven: Our blockbuster drugs could diffuse the expense but now with precision we can’t diffuse the expense over a large number of patients

President’s Cancer Panel Recommendation

Six recommendations

  1. promoting value based pricing
  2. enabling communications of cost
  3. financial toxicity
  4. stimulate competition biosimilars
  5. value based care
  6. invest in biomedical research

Patrick: the government pricing regime is hurting.  Alot of practical barriers but Merck has over 200 studies on cost basis

Robert:  many concerns/impetus started in Europe on pricing as they are a set price model (EU won’t pay more than x for a drug). US is moving more to outcomes pricing. For every one health outcome study three studies did not show a benefit.  With cancer it is tricky to establish specific health outcomes.  Also Medicare gets best price status so needs to be a safe harbor for payers and biggest constraint is regulatory issues.

Steven: They all want value based pricing but we don’t have that yet and there is a challenge to understand the nuances of new therapies.  Hard to align all the stakeholders together so until some legislation starts to change the reimbursement-clinic-patient-pharma obstacles.  Possibly the big data efforts discussed here may help align each stakeholders goals.

Gary: What is the data necessary to understand what is happening to patients and until we have that information it still will be complicated to determine where investors in health care stand at in this discussion

Robert: on an ICER methods advisory board: 1) great concern of costs how do we determine fair value of drug 2) ICER is only game in town, other orgs only give recommendations 3) ICER evaluates long term value (cost per quality year of life), budget impact (will people go bankrupt)

4) ICER getting traction in the public eye and advocates 5) the problem is ICER not ready for prime time as evidence keeps changing or are they keeping the societal factors in mind and they don’t have total transparancy in their methodology

Steven: We need more transparency into all the costs associated with the drug and therapy and value-based outcome.  Right now price is more of a black box.

Moderator: pointed to a recent study which showed that outpatient costs are going down while hospital based care cost is going rapidly up (cost of site of care) so we need to figure out how to get people into lower cost setting

Breaking Down Silos in Research

“Silo” is healthcare’s four-letter word. How are researchers, life science companies and others sharing information that can benefit patients more quickly? Hear from experts at institutions that are striving to tear down the walls that prevent data from flowing.

Moderator: Vini Jolly, Executive Director, Woodside Capital Partners
Speakers:
Ardy Arianpour, CEO & Co-Founder, Seqster @seqster
Lauren Becnel, Ph.D., Real World Data Lead for Oncology, Pfizer
Rakesh Mathew, Innovation, Research, & Development Lead, HealthShareExchange
David Nace M.D., Chief Medical Officer, Innovaccer

Seqster: Seqster is a secure platform that helps you and your family manage medical records, DNA, fitness, and nutrition data—all in one place. Founder has a genomic sequencing background but realized sequence  information needs to be linked with medical records.

HealthShareExchange.org :

HealthShare Exchange envisions a trusted community of healthcare stakeholders collaborating to deliver better care to consumers in the greater Philadelphia region. HealthShare Exchange will provide secure access to health information to enable preventive and cost-effective care; improve quality of patient care; and facilitate care transitions. They have partnered with multiple players in healthcare field and have data on over 7 million patients.

Innovacer

Data can be overwhelming, but it doesn’t have to be this way. To drive healthcare efficiency, we designed a modular suite of products for a smooth transition into a data-driven world within 4 weeks. Why does it take so much money to move data around and so slowly?

What is interoperatibility?

Ardy: We knew in genomics field how to build algorithms to analyze big data but how do we expand this from a consumer standpoint and see and share your data.

Lauren: how can we use the data between patients, doctors, researchers?  On the research side genomics represent only 2% of data.  Silos are one issue but figuring out the standards for data (collection, curation, analysis) is not set. Still need to improve semantic interoperability. For example Flatiron had good annotated data on male metastatic breast cancer.

David: Technical interopatabliltiy (platform), semantic interopatability (meaning or word usage), format (syntactic) interopatibility (data structure).  There is technical interoperatiblity between health system but some semantic but formats are all different (pharmacies use different systems and write different prescriptions using different suppliers).  In any value based contract this problem is a big issue now (we are going to pay you based on the quality of your performance then there is big need to coordinate across platforms).  We can solve it by bringing data in real time in one place and use mapping to integrate the format (need quality control) then need to make the data democratized among players.

Rakesh:  Patients data should follow the patient. Of Philadelphia’s 12 health systems we had a challenge to make data interoperatable among them so tdhey said to providers don’t use portals and made sure hospitals were sending standardized data. Health care data is complex.

David: 80% of clinical data is noise. For example most eMedical Records are text. Another problem is defining a patient identifier which US does not believe in.

 

 

 

 

Please follow on Twitter using the following #hash tags and @pharma_BI

#MCConverge

#cancertreatment

#healthIT

#innovation

#precisionmedicine

#healthcaremodels

#personalizedmedicine

#healthcaredata

And at the following handles:

@pharma_BI

@medcitynews

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