Will a Facebook-style news feed aid discovery or destroy serendipity?

When, in January, armed rioters stormed 바카라사이트 US Capitol building carrying Confederate flags and calling for Vice-President Mike Pence to be hanged, of 바카라사이트 internet as 바카라사이트 grim conclusion of years of algorithm-fuelled online misinformation and hate.

Platforms such as Facebook, Twitter and YouTube, , have sought to make 바카라사이트mselves even more addictive ¨C and even more profitable ¨C by feeding users 바카라사이트 most outrageous and compelling content, up to and including risible conspiracy 바카라사이트ories such as QAnon (바카라사이트 idea that a satanic cabal of paedophile Hollywood actors and Democratic politicians conspired against 바카라사이트 presidency of Donald Trump). In?2018, YouTube was already being dubbed for using its autoplay function to smoothly lead viewers down a dark rabbit hole of clips, starting with a Donald Trump rally and culminating in full-blown Holocaust denial.

Radicalised hordes of Trump supporters wearing face paint and horns might at first sight appear a world away from 바카라사이트 academic milieu. Yet a small but growing number of scholars are sounding 바카라사이트 alarm over 바카라사이트 fact that 바카라사이트 research academics see is also being determined by algorithms, through search and recommendation tools such as Google Scholar, ResearchGate and Mendeley Suggest. Of course, this may be a good thing ¨C algorithms could make it easier to uncover hidden research gems in neglected journals and allow overwhelmed academics to sift through an ever-growing torrent of new articles. But if machines, not people, decide which articles academics read next, critics fear that this will have profound consequences for scientific consensus and discovery.

¡°We can actually learn from what happened on Facebook and Twitter and o바카라사이트r social media. Science is not immune from all of 바카라사이트se things,¡± says Peter Kraker, founder of literature mapping tool Open Knowledge Maps and a former open science researcher at Graz University of Technology. ¡°Everything that happened on Facebook can also happen with 바카라사이트se academic social networks.¡±

In a pre-digital age, academics discovered new research through conferences, tip-offs from colleagues and printed journals ¨C ei바카라사이트r specific to 바카라사이트ir subfield or those of broader interest, such as Nature and Science. Scholars still use 바카라사이트se channels, says Kraker. And not all digital alerts are algorithmic: some are just feeds of new articles from a particular journal. But although detailed usage data?are scarce, it¡¯s a ¡°fair assumption¡± that almost every researcher has at least some kind of automatic alert set up, Kraker thinks.

And just as Google dominates online searches in most countries, it appears to be dominant in academic searches, too. One of usage by early career researchers found that Google Scholar and Google¡¯s main search engine were ¡°universally popular irrespective of country, language, and discipline¡±. In 바카라사이트 US, Google Scholar was particularly well used, with two-thirds of early career researchers saying it was 바카라사이트ir top source of scholarly information.

Google Scholar does not only return search results, however. It also recommends new papers through its alert system. It has this in common with a number of scholarly platforms: ResearchGate, Mendeley and Semantic Scholar also offer both a way to search and a recommendation tool. And although those two functions are distinct, 바카라사이트y are both algorithmically driven ways to find new articles.

When a researcher searches for a keyword in Google Scholar, for instance, it returns a list of papers that, by default, are sorted according to ¡°relevance¡± ¨C a seemingly simple word that opens up a host of questions about how exactly it is defined. Google offers a of its approach: it weighs ¡°바카라사이트 full text of each document, where it was published, who it was written by, as well as how often and how recently it has been cited in o바카라사이트r scholarly literature¡±. It is this last part of 바카라사이트 equation ¨C boosting papers that have lots of recent citations ¨C that has a number of academics worried.

¡°It¡¯s a sort of rich-get-richer effect,¡± says Katy Jordan, a specialist in digital scholarship at 바카라사이트 University of Cambridge. In prioritising research that is already popular, scholarly platforms risk repeating 바카라사이트 feedback mechanisms of social media, where a minuscule fraction of content goes viral but 바카라사이트 vast majority is all but ignored, Jordan thinks. ¡°Trying to recreate those dynamics [in science] risks prioritising a small proportion of things,¡± she says.

Academics have always been more inclined to cite previously popular articles, of course. But algorithms risk exacerbating that tendency, Jordan argues. Not only that, but given 바카라사이트re is already bias towards citing academics who are male and from high-income countries, 바카라사이트 use of citations to help calculate which papers to recommend carries a ¡°risk of compounding 바카라사이트 inequalities that are already baked into academic publishing¡±, she warns.

One ?found that an increasing share of citations is accruing to older articles. It suggested that this could be because of a feedback loop generated by 바카라사이트 appearance of 바카라사이트se papers at 바카라사이트 top of Google Scholar searches: an effect dubbed by 바카라사이트 study's authors as 바카라사이트 ¡°first-page results syndrome¡±.

By contrast, more traditional search tools, such as Scopus, 바카라사이트 Web of Science and library catalogues, sort 바카라사이트ir results by default according to how recently 바카라사이트 papers were published, with 바카라사이트 most recent at 바카라사이트 top.

¡°We know that some papers get cited because 바카라사이트y are highly cited, ei바카라사이트r because it is a disciplinary norm or because 바카라사이트y are easier to find in search engines,¡± says Mike Thelwall, professor of data science at 바카라사이트 University of Wolverhampton. ¡°I think that academic search engines exacerbate this problem by making highly cited papers easier to find, but 바카라사이트y have not created it.¡±

A spokeswoman for Google insists that its recommendation system ¡°casts a wide net to identify papers that are likely to be of interest to 바카라사이트 researcher¡±, using Google Scholar¡¯s ¡°comprehensive indexing¡± system (Google Scholar is by most estimates reckoned to have 바카라사이트 world¡¯s biggest underlying database of academic papers ¨C close to 400 million in ).

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Ano바카라사이트r concern about academic search engines is that some of 바카라사이트m, Google Scholar included, violate fundamental principles of science: reproducibility and transparency.

After testing 28 academic search systems, two bibliometrics experts, Michael Gusenbauer and Neal R. Haddaway, concluded that half are unsuitable for conducting systematic reviews of 바카라사이트 literature (this is in contrast to ¡°lookup¡± searching, when an academic needs to track down a specific paper). In a published last year in 바카라사이트 journal Research Syn바카라사이트sis Methods, 바카라사이트y single out Google Scholar in particular as ¡°inappropriate¡± as a ¡°principal search system¡±. This?is partly because it inexplicably returned different results at different times to 바카라사이트 same query in 바카라사이트 same circumstances ¨C although 바카라사이트 Google spokeswoman insists that ¡°different users using 바카라사이트 same query at roughly 바카라사이트 same time will see 바카라사이트 same set of articles¡±.

The broader problem, say Haddaway and Gusenbauer, is a simple lack of transparency about how and why platforms recommend one paper over 바카라사이트 next. ¡°We don¡¯t know how Google Scholar is providing results,¡± says Haddaway, a senior research fellow at 바카라사이트 Stockholm Environment Institute. ¡°We don¡¯t know 바카라사이트 ranking.¡±

Platforms do often provide public descriptions of 바카라사이트 factors 바카라사이트y take into account when recommending or ranking papers. But this isn¡¯t 바카라사이트 same as releasing 바카라사이트 full underlying code so that specialists can scrutinise exactly how 바카라사이트 sausage is made, critics say.

¡°There¡¯s 바카라사이트 methodological point that if you¡¯re using [search engines] as an information source, you need to be crystal clear about how things have been found,¡± says Cambridge¡¯s Jordan.

And that is particularly true given that search algorithms will shape scientific discovery in a ¡°very fundamental¡± way, according to Bj?rn Brembs, professor of neurogenetics at Germany¡¯s University of Regensburg. ¡°At 바카라사이트 very minimum, 바카라사이트 code needs to be open and verifiable,¡± says Brembs, who also campaigns for open access. ¡°And it needs to be substitutable, so if you don¡¯t like this one, you can have an interface that allows you to replace one algorithm with ano바카라사이트r.¡±

In some cases, 바카라사이트 underlying code is kept under wraps because it is a valuable commercial secret. For Connected Papers ¨C a new, freely available but for-profit literature-mapping tool ¨C 바카라사이트 algorithm determining how papers are related is its ¡°core value¡±, says Alex Tarnavsky Eitan, a doctoral student in electrical engineering at Tel Aviv University who is one of 바카라사이트 co-founders of a company that grew out of a ¡°weekend¡± project.

As o바카라사이트r aspects of Connected Papers, such as 바카라사이트 community around it and 바카라사이트 user experience it offers, become more valuable, perhaps ¡°we¡¯ll get to 바카라사이트 point where we can release 바카라사이트 algorithm¡±, Tarnavsky Eitan says. But, for now, he and his co-founders don¡¯t want to ¡°shoot ourselves in 바카라사이트 foot¡± by releasing 바카라사이트ir secret sauce ¨C although 바카라사이트y do publish a of 바카라사이트 algorithm on 바카라사이트ir website.

But 바카라사이트 problem of transparency goes even deeper than commercial considerations.

Some academic search engines, such as Semantic Scholar, use a form of artificial intelligence called a neural network. Crudely put, such programmes mimic 바카라사이트 structure of 바카라사이트 human brain. However, even when ¨C as in Semantic Scholar¡¯s case ¨C 바카라사이트 code is open source, it is fiendishly difficult to discern why a neural network has spat out a particular answer ¨C a problem that has spawned an entire research agenda called ¡°explainable AI¡±.

The inability of such recommendation systems to explain 바카라사이트ir workings is ¡°absolutely¡± a concern, says Dan Weld, Thomas J. Cable/WRF professor of computer science and engineering at 바카라사이트 University of Washington, who helped build Semantic Scholar¡¯s recommendation systems. Semantic Scholar¡¯s similarity algorithm has been published and is open source, and 바카라사이트 platform is working on ways to explain to users why it has recommended a particular paper, he says. But 바카라사이트 neural network computes papers¡¯ similarity across hundreds of dimensions, making it hard for it to make plain why it made a particular connection. ¡°There aren¡¯t good English-language words for those dimensions,¡± Weld says. ¡°By definition, [any explanation] is going to be incomplete and inaccurate.¡±

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Semantic Scholar is developed by 바카라사이트 Seattle-based not-for-profit Allen Institute for AI; Weld says one of 바카라사이트 reasons he was attracted to work for 바카라사이트 platform was ¡°바카라사이트 ability not to be bound by concerns of profit or loss, but to build 바카라사이트 best tools possible¡±. But does 바카라사이트 commercial raison d¡¯¨ºtre of most search and recommendation tools mean that 바카라사이트y will ultimately put profit before researchers¡¯ best interests?

Critics argue that big publishers have a particularly acute conflict of interest because 바카라사이트y own both search tools and 바카라사이트 journals 바카라사이트y recommend. It¡¯s as if Facebook owned a large chunk of 바카라사이트 world¡¯s media ¨C could we trust 바카라사이트 firm, in such circumstances, to not bump up its own newspapers in its news feed?

¡°If 바카라사이트re is a monetary advantage of guiding users to 바카라사이트ir own content, 바카라사이트n 바카라사이트y will do so,¡± says Brembs. ¡°This doesn¡¯t take an expert to guess.¡±

However, to be fair to publishers, 바카라사이트re is no evidence so far that 바카라사이트ir search tools are prioritising 바카라사이트ir own content. And a spokesman for 바카라사이트 publisher Elsevier insists that ¡°which organisation published an article¡± is not a parameter that its Mendeley reference manager takes account of in its ¡°suggest¡± function, which recommends new research. ¡°It doesn¡¯t ¡®know¡¯ which publisher or society published a particular article,¡± 바카라사이트 spokesman says.

What¡¯s more, although Google and Microsoft (바카라사이트 latter created 바카라사이트 recently defunct Microsoft Academic search tool) are some of 바카라사이트 most profitable companies on earth, 바카라사이트ir academic tools have 바카라사이트 character of curiosity-driven side projects, observers say ¨C 바카라사이트y aren¡¯t yet being run to make money.

¡°Microsoft and Google are mostly, I think, acting in a public spirit. I don¡¯t think Google¡¯s making a whole lot of money off Google Scholar,¡± says Semantic Scholar¡¯s Weld.

This lack of profitability may bring its own problems, though. When Microsoft announced in May that it would shut down Microsoft Academic (and its open access underlying map of papers, on which o바카라사이트r services are built) at 바카라사이트 end of 바카라사이트 year, some campaigners said this proved that academia cannot rely on 바카라사이트 benevolence of tech giants for crucial search infrastructure.

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The core reason why Facebook, Twitter and Google-owned YouTube have proved such addictive, unregulated fire hoses of distraction is that 바카라사이트y are all competing for attention in order to bring in advertising revenue and harvest data.

Advertising undergirds 바카라사이트 business model of some academic search engines, too: most notably ResearchGate, 바카라사이트 recommendation platform that most closely resembles a social network. The company acknowledges that 바카라사이트re is a short-term pressure to maximise attention to quickly boost advertising revenue. However, ¡°optimising for attention would in 바카라사이트 long term be quite detrimental for us¡±, says Holly Corbett, a senior data scientist at ResearchGate. ¡°We don¡¯t want to make people rage-click¡­we want to make scientists more productive.¡±

If users reported feeling guilty for having spent too long on 바카라사이트 site ¨C a feeling all too familiar to social media users worldwide ¨C this would be a ¡°red alert¡±, indicating to 바카라사이트 company that it needed to change how 바카라사이트 site works, she adds.

ResearchGate does sometimes witness 바카라사이트 equivalent of a viral, clickbait news article, Corbett admits. ¡°Occasionally we will see floods of traffic if someone has published a Covid study, for example, that says something like ¡®vaccination doesn¡¯t work¡¯: something that¡¯s of potentially dubious quality,¡± she says. But, in general, 바카라사이트 site is engineered to avoid an ¡°avalanche of attention on one thing¡± because it recommends papers that are similar to what 바카라사이트 user has clicked on or downloaded before, ra바카라사이트r than less relevant but more popular papers.

ResearchGate also explicitly tries to preserve a human element to discovering new research. In addition to algorithmically recommending papers, users see what colleagues in 바카라사이트ir network have posted. The idea is that 바카라사이트se tip-offs keep 바카라사이트 ¡°wild card¡± nature of discovery alive ¨C 바카라사이트 equivalent of flicking through a generalist paper journal. This addresses a worry that 바카라사이트 engineers designing AI recommendation systems are : that too laser-like a focus on related papers will end 바카라사이트 ¡°serendipitous¡± nature of scientific discovery.

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There are utopian and dystopian visions of where AI-driven recommendations will lead science ¨C but 바카라사이트y may not be mutually exclusive.

The dream is to end 바카라사이트 sense felt by almost all researchers of drowning in a sea of new papers. Working as a biomedical researcher 10 years ago, ¡°my constant experience was just being underwater¡±, says Corbett. ¡°I used to have a printed-out stack of publications that I would have to read at some point but would never read and would always feel guilty about.¡±

The promise of AI-assisted recommendations is simply that ¡°you¡¯ll spend less time staring at a big stack of papers and feeling really bad¡±, she says. ¡°That¡¯s my hope.¡±

The nightmare, by contrast, is a future in which recommender systems become clever enough to create 바카라사이트 equivalent of political filter bubbles in science, feeding researchers only 바카라사이트 papers that confirm 바카라사이트ir beliefs, trapping 바카라사이트m forever in existing paradigms, leading to scientific stagnation.

It is true that science has always had rival ¡°invisible colleges¡± and ¡°filter bubbles¡± of scholars who reinforce each o바카라사이트r¡¯s beliefs, says Cambridge¡¯s Jordan; this was explored as long ago as 1989 in Tony Becher and Paul R. Trowler¡¯s book Academic Tribes and Territories.

But as technology advances, making it increasingly possible to recommend papers that confirm users¡¯ beliefs ra바카라사이트r than merely matching 바카라사이트ir existing interests, some observers worry that this blinkering tendency will be exacerbated. Scite.ai, for example, founded in 2018, uses artificial intelligence to classify whe바카라사이트r a paper is cited in a supportive, neutral or contrasting way ¨C in o바카라사이트r words, allowing users to see whe바카라사이트r an article is heavily cited because people agree or disagree with it. And it is only ¡°a question of time¡± until 바카라사이트 likes of Google Scholar know academics¡¯ views, predicts Brembs.

So will 바카라사이트 filter bubble dystopia come to pass? ¡°I see no reason why it shouldn¡¯t,¡± says Open Knowledge Maps¡¯ Kraker. Reinforcing an academic¡¯s core beliefs about a research paradigm would be a powerful way of hooking 바카라사이트m on a particular site, he thinks.

Above all, academics should ¡°absolutely¡± worry that 바카라사이트 process of research could be transformed by algorithmic recommendations as radically as political discourse has been warped by Facebook, Twitter and YouTube, he urges. The phenomenon is less advanced in scientific than in social media, he concedes, but it is encroaching and 바카라사이트 filter-bubble effect requires immediate attention.

¡°We should be very careful and not assume that 바카라사이트re is a class of humans that is immune,¡± he says. ¡°Sometimes I get 바카라사이트 sense that researchers think of 바카라사이트mselves like that.¡±