citations

Page rank of scientific papers with citation in Wikidata – so far

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A citation property has just be created a few hours ago, – and as of writing still not been deleted. It means we can describe citation network, e.g., among scientific papers.

So far we have added a few citations, – mostly from papers about Zika. And now we can plot the citation network or compute the network measures such as page rank.

Below is a Python program using everything with Sparql, Pandas and NetworkX:

statement = """
select ?source ?sourceLabel ?target ?targetLabel where {
  ?source wdt:P2860 ?target .
  SERVICE wikibase:label {
    bd:serviceParam wikibase:language "en" .
  }
} 
"""

service = sparql.Service('https://query.wikidata.org/sparql')
response = service.query(statement)
df = DataFrame(response.fetchall(),
    columns=response.variables)

df.sourceLabel = df.sourceLabel.astype(unicode)
df.targetLabel = df.targetLabel.astype(unicode)

g = nx.DiGraph()
g.add_edges_from(((row.sourceLabel, row.targetLabel)
    for n, row in df.iterrows()))

pr = nx.pagerank(g)
sorted_pageranks = sorted((rank, title)
    for title, rank in pr.items())[::-1]

for rank, title in sorted_pageranks[:10]:
    print("{:.4} {}".format(rank, title[:40]))

The result:

0.02647 Genetic and serologic properties of Zika
0.02479 READemption-a tool for the computational
0.02479 Intrauterine West Nile virus: ocular and
0.02479 Internet encyclopaedias go head to head
0.02479 A juvenile early hominin skeleton from D
0.01798 Quantitative real-time PCR detection of 
0.01755 Zika virus. I. Isolations and serologica
0.01755 Genetic characterization of Zika virus s
0.0175 Potential sexual transmission of Zika vi
0.01745 Zika virus in Gabon (Central Africa)--20
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Using Google Web-service to keep track of scientific citations to me

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Googlescholar

Google Scholar allows me to see which scientific papers cite my scientific papers. However, it does not order them according to date so I cannot easily identify the most recent papers with cite to me.

One way to somehow identify recent citations is to use the “as_ylo” parameter available in the advanced search. With as_ylo=2009 only the papers published in 2009 are shown to the given query. Combining that with a negative ‘author:’ query gets you some of the way, e.g., with “Nielsen FA” -author:”FA Nielsen” (included as_ylo=2009) I find papers from 2009 mentioning ‘Nielsen FA’ that are not authored by me.

To get a higher retrieval rate I list some of the different variations of my name in the query. The real query is then (abbreviated) “Nielsen FA” OR … -author:”FA Nielsen” …!

As the year progresses one gets more and more citations and it becomes difficult to identify the new ones. Using the real-time search in the standard Google Web search one may try an alternative way. Restricting the search to PDF files and real-time search for past month data may result in newer data, – but probably also lacking papers from publishers letting Google Scholar in but Google Web out: “Nielsen FA” OR … filetype:pdf

It is possible that Google Alerts also can help.

2010-11-25: Typo correction