Recommendation mechanism to review


Hello, everybody! I’m a student in Huazhong university of science and techology in China. As far as we know, a sutiable reviewer is excellent helpful to your paper, no matter whether your paper accepeted or not. There is no doubting that Choosing the reviewer just relying on the empirical is inefficient. Fox example, there are nearly 6088 editors in PLOS ONE journal and it is not an easy thing to choose the editor who know your paper best. Therefore, a thought arise in my mind
that whether we can build a recommendation mechanism to help us find the most sutiable review?

ROpenSci supplies an access to all the airticles punished in the Plos One journal, moreover, expertise information for every editor can also be obtain in the homepage of the journal. Based on the information in the articles (including the abstract, key word, main body and references) and expertise information, whether we can build a bridge to link the two?

Any comment is welcome and hope somebody can help me solve the problem!


Hi there - Some questions:

Do you mean something like: If so, that info isn’t in the API as far as I know, but it could be scraped separately. I suppose you can glean something from their focus areas, but there’s no other info about each editor.

We can get lots of data on each article, including the editor name, from the rplos package, e.g, here we just get the DOI and the editor (in your case you probably want to also get abstract, and other parts of the article - note that keywords are not provided in the API)

searchplos(q='ecology', fl=c('id','editor'), 
           fq=list('-article_type:correction','-article_type:viewpoints'), limit = 15)
  numFound start maxScore
1    24941     0       NA

                             id                   editor
1  10.1371/journal.pone.0059813      Luís A Nunes Amaral
2  10.1371/journal.pone.0001248  Minna-Liisa Rantalainen
3  10.1371/journal.pone.0080763         Joanna E Lambert
4  10.1371/journal.pone.0102437        Ben Bond-Lamberty
5  10.1371/journal.pone.0017342              Thomas Bell
6  10.1371/journal.pcbi.1003594         Jonathan A Eisen
7  10.1371/journal.pbio.0020072                     none
8  10.1371/journal.pbio.1001702          Georgina M Mace
9  10.1371/journal.pone.0111996          Diego Fontaneto
10 10.1371/journal.pone.0054689 Kimberly Patraw Van Niel
11 10.1371/journal.pone.0074321               Sam Dupont
12 10.1371/journal.pbio.1001248            Michel Loreau
13 10.1371/journal.pbio.0000073                     none
14 10.1371/journal.pbio.0060300           Anurag Agrawal
15 10.1371/journal.pone.0057786          Nicolas Chaline