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In the below code, the estimated h-index of authors is calculated.

library(bibliometrix)
results <- biblioAnalysis(df, sep = ";")
indices$CitationList
authors=gsub(","," ",names(results$Authors)[1:10])
indices <- Hindex(M16, field = "author", elements=authors, sep = ";", years = 50)

Then outputted onto a table, like the one below using indices$H

      Author h_index g_index m_index TC NP PY_start
1     TSAI CC       6       8     1.2 69 11     2016
2  ZEMBYLAS M       5       7     1.0 60 11     2016
3   BOGNER FX       4       6     0.8 43 10     2016
4       KIM H       3       4     0.6 22 10     2016
5       KIM J       5       9     1.0 82 10     2016
6      WANG J       3       3     0.6 21 10     2016
7       LEE J       2       5     0.4 27  9     2016
8   MARTIN AJ       3       6     0.6 45  8     2016
9    TAYLER C       4       6     0.8 38  8     2016
10    COHEN A       2       4     0.4 24  7     2016

The issue I have is with common names like LEE J on row 7. How do I identify, from the results data, this specific LEE J? Thanks for help!

massisenergy
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Ian Hargreaves
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  • Sorry, I didn't make it clear - I didn't want to subset the data within `indIces$h`, I wanted to subbed LEE J's data from the `results` object, created in the previous lines. – Ian Hargreaves Feb 22 '20 at 21:04
  • Can you show a `dput` of few lines of `df` – akrun Feb 22 '20 at 21:06
  • Something like `indices$H[indices$H$Author == "LEE J", ]` might work. But as akrun said, `dput` of `df` would be helpful. – Kevin Cazelles Feb 22 '20 at 21:34

1 Answers1

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The results would be a list object and Authors is a frequency table of counts with names as author name. If that is case, we can use grep to identify names with substring matches for 'LEE J'

i1 <- grep("LEE J", names(results$Authors))
results$Authors[i1]

Or use == for exact matches

results$Authors[names(results$Authors) == "LEE J"]
akrun
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