publication networks

---

1 getting started

Start with clean workspace

rm(list = ls())

---

2 Goal

Our goal is to make a network based on the publications we scraped for our scholars.

3 Custom functions

• fpackage.check: Check if packages are installed (and install if not) in R (source).
  
• fsave: Save to processed data in repository
  
• fload: To load the files back after an fsave
  
• fshowdf: To print objects (tibbles / data.frame) nicely on screen in .rmd

fpackage.check <- function(packages) {
    lapply(packages, FUN = function(x) {
        if (!require(x, character.only = TRUE)) {
            install.packages(x, dependencies = TRUE)
            library(x, character.only = TRUE)
        }
    })
}

fsave <- function(x, file = NULL, location = "./data/processed/") {
    ifelse(!dir.exists("data"), dir.create("data"), FALSE)
    ifelse(!dir.exists("data/processed"), dir.create("data/processed"), FALSE)
    if (is.null(file))
        file = deparse(substitute(x))
    datename <- substr(gsub("[:-]", "", Sys.time()), 1, 8)
    totalname <- paste(location, datename, file, ".rda", sep = "")
    save(x, file = totalname)  #need to fix if file is reloaded as input name, not as x. 
}

fload <- function(filename) {
    load(filename)
    get(ls()[ls() != "filename"])
}

fshowdf <- function(x, ...) {
    knitr::kable(x, digits = 2, "html", ...) %>%
        kableExtra::kable_styling(bootstrap_options = c("striped", "hover")) %>%
        kableExtra::scroll_box(width = "100%", height = "300px")
}

4 packages

• stringdist: string stuff.
• stringi: string stuff

packages = c("stringdist", "stringi", "tidyverse")

fpackage.check(packages)

5 load data

Hopefully you managed to construct the datasets yourself. If not. Here are the downloads:

Please use this one:

Download 20230621df_complete.rda.

Download 20230621list_publications_jt.rda.

Save file in correct directory: ‘./data/processed’.

As a brief update:

• we have a dataset of scholars, with all kind of interesting info at the ego-level
  
• for each scholar we have a list of all publications, including the co-authors

Thus based on these egonets we have to construct a ‘complete network’.

Important question for complete network data: What is our sampling unit?

df <- fload("./data/processed/20230621df_complete.rda")
publications <- fload("./data/processed/20230621list_publications_jt.rda")

5.1 unique publications in df

publications <- publications %>%
    bind_rows() %>%
    distinct(title, .keep_all = TRUE)

---

6 networks based on publications

We have to make a couple of decisions:

• what are the boundaries of our network?:
  • combination of university and discipline
    
• undirected or directed network?:
  • directed: first author is sending a tie to other authors
    
• weighted or unweighted network?:
  • unweighted (no distinction between number ties within a specific time window, thus 0/1)
    
• time window?:
  • one wave is 3 years
    
  • 2 waves
    • wave 1: 2018-2020
      
    • wave 2: 2021-2023

6.1 An example: RU-sociology

# select scholars
df %>%
    filter(affil1 == "RU" | affil2 == "RU") %>%
    filter(discipline == "sociology") -> df_sel
fshowdf(df_sel)

id	uni	discipline	year	name	affil1	affil2	position	np	lastname	firstname	ini	gender	gs_id	gs_name	gs_homepage	gs_field	gs_i10_index	gs_h_index	gs_total_cites	gs_affiliation
471b42	RU	sociology	2022	Ronald Batenburg	RU		full_prof		batenburg	ronald		male	UK7nVSEAAAAJ	Ronald Batenburg	https://www.nivel.nl/nl/ronald-batenburg	Gezondheidszorg	94	33	4306	Programmaleider NIVEL en bijzonder hoogleraar Radboud Universiteit Nijmegen
31144d	RU	sociology	2022	Katia Begall	RU		assistant_prof		begall	katia		female	e7zfTqMAAAAJ	Katia Begall	NA	family sociology	9	9	1268	Radboud University Nijmegen
888093	RU	sociology	2022	Hidde Bekhuis	RU		other		bekhuis	hidde		male	Q4saWX8AAAAJ	Hidde Bekhuis	NA	Sociologie	9	9	458	Post Doc Sociology, Radboud University Nijmegen
c47638	RU	sociology	2022	Lonneke van den Berg	RU		postdoc	van den	berg	lonneke		female	vzBNQ1kAAAAJ	Lonneke van den Berg	https://lonnekevandenberg.com/	Family sociology	3	5	79	Netherlands Interdisciplinary Demographic Institute (NIDI)
f99757	RU	sociology	2022	Lieselotte Blommaert	RU		assistant_prof		blommaert	lieselotte		female	RG54uasAAAAJ	Lieselotte Blommaert	http://www.ru.nl/english/people/blommaert-e/	Labor market	11	11	479	Sociology/Social Cultural Research, Radboud University, Nijmegen, the
7e85d6	RU	sociology	2022	Rob Eisinga	RU		assistant_prof		eisinga	rob		male	GDHdsXAAAAAJ	Rob Eisinga	http://robeisinga.ruhosting.nl/	research methods	83	35	6401	Professor social science research methods, Radboud University Nijmegen
5f9d45	RU	sociology	2022	Maurice Gesthuizen	RU		assistant_prof		gesthuizen	maurice		male	n6hiblQAAAAJ	Maurice Gesthuizen	NA	Sociology	45	28	2972	Assistant professor
3e9d6d	RU	sociology	2022	Nella Geurts	RU		postdoc		geurts	nella		female	VCTvbTkAAAAJ	Nella Geurts	NA	Sociology	3	4	90	Department of Sociology, Radboud University
7f8ff4	RU	sociology	2022	Saskia Glas	RU		assistant_prof		glas	saskia		female	ZMc0j2YAAAAJ	Saskia Glas	NA	Gender	6	7	223	Assistant Professor (tenured), Radboud University
6075fe	RU	sociology	2022	Margriet van Hek	RU		assistant_prof	van	hek	margriet		female	ZvLlx2EAAAAJ	Margriet van Hek	NA	Sociology	10	10	487	Radboud University
2d4a95	RU	sociology	2022	Remco Hoekman	RU		other		hoekman	remco		male	LsMimOEAAAAJ	Remco Hoekman	https://www.mulierinstituut.nl/over-mulier/medewerkers/remco-hoekman/	sport sociology	17	13	918	Director, Mulier Institute / Senior researcher, Radboud University
61b8a6	RU	sociology	2022	Bas Hofstra	RU		assistant_prof		hofstra	bas		NA	Nx7pDywAAAAJ	Bas Hofstra	http://www.bashofstra.com/	Sociology of science	10	10	966	Assistant Professor, Radboud University
07b8a5	RU	sociology	2022	Judith Koops	RU		postdoc		koops	judith		female	kLiOlQoAAAAJ	Judith C. Koops	NA	family demography	4	6	110	Dr. Family Demographer, Radboud University
1bf89e	RU	sociology	2022	Gerbert Kraaykamp	RU		full_prof		kraaykamp	gerbert		male	l8aM4jAAAAAJ	Gerbert Kraaykamp	https://www.ru.nl/english/people/kraaykamp-g/	social stratification	107	51	9279	Professor of Sociology, Radboud Universiteit Nijmegen
f618fc	RU	sociology	2022	Roza Meuleman	RU		assistant_prof		meuleman	roza		female	iKs_5WkAAAAJ	Roza Meuleman	NA	Cultural Sociology	10	10	308	Assistant Professor - Sociology - Radboud University Nijmegen
dad54c	RU	sociology	2022	Michael Savelkoul	RU		assistant_prof		savelkoul	michael		male	_f3krXUAAAAJ	Michael Savelkoul	NA	NA	9	9	722	Assistant Professor - Sociology, Radboud University Nijmegen, the Netherlands
a576d6	RU	sociology	2022	Peer Scheepers	RU		full_prof		scheepers	peer		male	hPeXxvEAAAAJ	peer scheepers	NA	sociale wetenschappen	190	64	16727	hoogleraar methodologie, faculteit der sociale wetenschappen radboud universiteit
5da2d4	RU	sociology	2022	Niels Spierings	RU		associate_prof		spierings	niels		male	cy3Ye6sAAAAJ	Niels Spierings	https://www.ru.nl/english/people/spierings-c/	politics	46	27	2673	Associate Professor of Sociology, Radboud University
07231a	RU/RUG	sociology	2022	Jochem Tolsma	RU	RUG	full_prof		tolsma	jochem		male	Iu23-90AAAAJ	Jochem Tolsma	http://www.jochemtolsma.nl/	social divisions between groups	38	25	2888	Professor, Radboud University Nijmegen / University of Groningen
b65f6f	RU	sociology	2022	Ellen Verbakel	RU		full_prof		verbakel	ellen		female	w2McVJAAAAAJ	Ellen Verbakel	http://www.ellenverbakel.nl/	Family	40	26	2242	Professor of Sociology, Department of Sociology, Radboud University Nijmegen
5e2898	RU	sociology	2022	Mark Visser	RU		assistant_prof		visser	mark		male	ItITloQAAAAJ	Mark Visser	https://www.researchgate.net/profile/Mark_Visser	life course	10	10	580	Assistant Professor, Radboud University
9ab0fc	RU	sociology	2022	Maarten Wolbers	RU		full_prof		wolbers	maarten		male	TqKrXnMAAAAJ	Maarten HJ Wolbers	http://www.socsci.ru.nl/maartenw/	school-to-work transitions	65	32	4380	Professor of Sociology, Radboud University, Nijmegen
6cca60	RU	sociology	2022	Carlijn Bussemakers	RU		phd		bussemakers	carlijn		female	bDPtkIoAAAAJ	Carlijn Bussemakers	NA	NA	3	3	102	Unknown affiliation
4ed5be	RU	sociology	2022	Rob Franken	RU		phd		franken	rob		male		NA	NA	NA	NA	NA	NA	NA
f92019	RU	sociology	2022	Mustafa Firat	RU		phd		firat	mustafa		male	rrh0V7IAAAAJ	NA	NA	NA	NA	NA	NA	NA
f782c2	RU	sociology	2022	Aysegül Güneyli	RU		phd		guneyli	aysegul		female		NA	NA	NA	NA	NA	NA	NA
513b49	RU	sociology	2022	Inge Hendriks	RU		phd		hendriks	inge		female		NA	NA	NA	NA	NA	NA	NA
e37333	RU	sociology	2022	Thijmen Jeroense	RU		phd		jeroense	thijmen		male	izq-KNUAAAAJ	Thijmen Jeroense	https://www.ru.nl/personen/jeroense-t/	Political Participation	1	2	15	PhD candidate, Radboud University Nijmegen
b672bd	RU	sociology	2022	Rachel Kollar	RU		phd		kollar	rachel		female	b96_CCUAAAAJ	Rachel Kollar	NA	Migration	2	2	49	PhD Candidate Radboud University, Nijmegen
ac8ab3	RU	sociology	2022	Nik Linders	RU		phd		linders	nik		male		NA	NA	NA	NA	NA	NA	NA
b6cedc	RU	sociology	2022	Renae Loh	RU		phd		loh	renae		female	tFaMPOQAAAAJ	Renae Sze Ming Loh	http://renaeloh.com/	sociology	2	4	182	PhD candidate, Radboud University
e2ebbb	RU	sociology	2022	Maikel Meijeren	RU		phd		meijeren	maikel		male		NA	NA	NA	NA	NA	NA	NA
a527b8	RU	sociology	2022	Carly van Mensvoort	RU		phd	van	mensvoort	carly		female	z6iMs-UAAAAJ	Carly van Mensvoort	https://www.ru.nl/english/people/mensvoort-c-van/	Gender inequality	2	3	48	Radboud University
1e61cb	RU	sociology	2022	Anne Maaike Mulders	RU		phd		mulders	anne		female		NA	NA	NA	NA	NA	NA	NA
554613	RU	sociology	2022	Katrin Müller	RU		phd		muller	katrin		female		NA	NA	NA	NA	NA	NA	NA
7c14e8	RU	sociology	2022	Klara Raiber	RU		phd		raiber	klara		female	xE65HUcAAAAJ	Klara Raiber	https://www.ru.nl/english/people/raiber-k/	informal care	1	4	44	PhD candidate, Radboud University Nijmegen
809f71	RU	sociology	2022	Marlou Ramaekers	RU		phd		ramaekers	marlou		female	fp99JAQAAAAJ	Marlou Ramaekers	NA	Sociology	0	2	7	Data Manager and Researcher
c1722b	RU	sociology	2022	Sara Wiertsema	RU		phd		wiertsema	sara		female	wgQQD6kAAAAJ	Sara Wiertsema	NA	Sociology	0	1	2	PhD candidate, Radboud University
a00209	RU	sociology	2022	Janos Betko	RU		phd		betko	janos		male	Cvdrl6AAAAAJ	Janos Betko	NA	welfare	0	5	37	Radboud University
8e7b43	RU	sociology	2022	Jansje van Middendorp	RU		phd	van	middendorp	jansje		female	gs0li6MAAAAJ	Jansje van Middendorp	NA	vrijwilligers	0	1	8	Buitenpromovendus Radboud Universiteit
91db4e	RU	sociology	2022	Elize Vis	RU		phd		vis	elize		female		NA	NA	NA	NA	NA	NA	NA
bb8ffa	RU	sociology	2022	Tijmen Weber	RU		phd		weber	tijmen		male	KfLALRIAAAAJ	Tijmen Weber	NA	Sociology	2	2	60	Lecturer Statistics and Research, HAN University of Applied Sciences
05a9d1	RU	sociology	2022	Elissa El Khawli	RU		other	el	khawli	elissa		female	2wDZZbsAAAAJ	Elissa El Khawli	NA	NA	2	3	27	Assistant Professor, Erasmus University Rotterdam
683c64	RU	sociology	2022	Carl Sterkens	RU		other		sterkens	carl		male		NA	NA	NA	NA	NA	NA	NA
e5d4c4	RU	sociology	2022	Paul Vermeer	RU		other		vermeer	paul		male		NA	NA	NA	NA	NA	NA	NA
0e20be	RU	sociology	2022	Malou Grubben	RU		other		grubben	malou		female		NA	NA	NA	NA	NA	NA	NA
1c7266	RUG/RU	sociology	2022	Marcel Lubbers	RUG	RU	full_prof		lubbers	marcel		male	078qsZoAAAAJ	Marcel Lubbers	https://www.uu.nl/staff/MLubbers	Nationalism	91	43	8010	Professor in Interdisciplinary Social Science | ERCOMER | Utrecht University

6.1.1 network based on publications

We will use an adjacency matrix to store our network ties: the first author is sending a tie to other authors.

We make the assumption that the composition of the network is stable!

networkw1 <- matrix(0, nrow = nrow(df_sel), ncol = nrow(df_sel))
networkw2 <- matrix(0, nrow = nrow(df_sel), ncol = nrow(df_sel))

6.1.2 select publications

# wave1
publications %>%
    filter(gs_id %in% df_sel$gs_id) %>%
    filter(year %in% c(2018, 2019, 2020)) -> pub_w1
nrow(pub_w1)

# wave2
publications %>%
    filter(gs_id %in% df_sel$gs_id) %>%
    filter(year %in% c(2021, 2022, 2023)) -> pub_w2
nrow(pub_w2)

#> [1] 324
#> [1] 289

6.1.3 make a list for each publication

cleaned a bit

# wave1
pub_w1 <- str_split(pub_w1$author, ",") %>%
    # lowercase
lapply(tolower) %>%
    # Removing diacritics
lapply(stri_trans_general, id = "latin-ascii") %>%
    # only last name
lapply(word, start = -1, sep = " ") %>%
    # only last last name
lapply(word, start = -1, sep = "-")

# let us remove all publications with only one author
remove <- which(sapply(pub_w1, FUN = function(x) length(x) == 1) == TRUE)
pub_w1 <- pub_w1[-remove]
length(pub_w1)

#> [1] 278

# wave2
pub_w2 <- str_split(pub_w2$author, ",") %>%
    # lowercase
lapply(tolower) %>%
    # Removing diacritics
lapply(stri_trans_general, id = "latin-ascii") %>%
    # only last name
lapply(word, start = -1, sep = " ") %>%
    # only last last name
lapply(word, start = -1, sep = "-")

# let us remove all publications with only one author
remove <- which(sapply(pub_w2, FUN = function(x) length(x) == 1) == TRUE)
pub_w2 <- pub_w2[-remove]
length(pub_w2)

#> [1] 250

6.1.4 find the author positions

And if we know the author positions, we can fill in our matrix

pubs <- pub_w1
for (ego in 1:nrow(df_sel)) {
    # which ego?
    lastname_ego <- df_sel$lastname[ego]
    # for all publications
    for (pub in 1:length(pubs)) {
        # only continue if ego is author of pub
        if (lastname_ego %in% pubs[[pub]]) {
            aut_pot <- which.max(pubs[[pub]] %in% lastname_ego)
            # only continue if ego is first author of pub
            if (aut_pot == 1) {
                # check all alters/co-authors
                for (alter in 1:nrow(df_sel)) {
                  # which alter
                  lastname_alter <- df_sel$lastname[alter]
                  if (lastname_alter %in% pubs[[pub]]) {
                    networkw1[ego, alter] <- networkw1[ego, alter] + 1
                  }
                }
            }
        }
    }
}


pubs <- pub_w2

for (ego in 1:nrow(df_sel)) {
    # which ego?
    lastname_ego <- df_sel$lastname[ego]
    # for all publications
    for (pub in 1:length(pubs)) {
        # only continue if ego is author of pub
        if (lastname_ego %in% pubs[[pub]]) {
            aut_pot <- which.max(pubs[[pub]] %in% lastname_ego)
            # only continue if ego is first author of pub
            if (aut_pot == 1) {
                # check all alters/co-authors
                for (alter in 1:nrow(df_sel)) {
                  # which alter
                  lastname_alter <- df_sel$lastname[alter]
                  if (lastname_alter %in% pubs[[pub]]) {
                    networkw1[ego, alter] <- networkw1[ego, alter] + 1
                  }
                }
            }
        }
    }
}

---

7 making life easy

Wouldn’t it be great if we could not write a function that would all this in one go?

Okay

f_pubnets <- function(df_scholars = df, list_publications = publications, discip = "sociology", affiliation = "RU",
    waves = list(wave1 = c(2018, 2019, 2020), wave2 = c(2021, 2022, 2023))) {

    publications <- list_publications %>%
        bind_rows() %>%
        distinct(title, .keep_all = TRUE)

    df_scholars %>%
        filter(affil1 == affiliation | affil2 == affiliation) %>%
        filter(discipline == discip) -> df_sel

    networklist <- list()
    for (wave in 1:length(waves)) {
        networklist[[wave]] <- matrix(0, nrow = nrow(df_sel), ncol = nrow(df_sel))
    }

    publicationlist <- list()
    for (wave in 1:length(waves)) {
        publicationlist[[wave]] <- publications %>%
            filter(gs_id %in% df_sel$gs_id) %>%
            filter(year %in% waves[[wave]]) %>%
            select(author) %>%
            lapply(str_split, pattern = ",")
    }

    publicationlist2 <- list()
    for (wave in 1:length(waves)) {
        publicationlist2[[wave]] <- publicationlist[[wave]]$author %>%
            # lowercase
        lapply(tolower) %>%
            # Removing diacritics
        lapply(stri_trans_general, id = "latin-ascii") %>%
            # only last name
        lapply(word, start = -1, sep = " ") %>%
            # only last last name
        lapply(word, start = -1, sep = "-")
    }

    for (wave in 1:length(waves)) {
        # let us remove all publications with only one author
        remove <- which(sapply(publicationlist2[[wave]], FUN = function(x) length(x) == 1) == TRUE)
        publicationlist2[[wave]] <- publicationlist2[[wave]][-remove]
    }

    for (wave in 1:length(waves)) {
        pubs <- publicationlist2[[wave]]
        for (ego in 1:nrow(df_sel)) {
            # which ego?
            lastname_ego <- df_sel$lastname[ego]
            # for all publications
            for (pub in 1:length(pubs)) {
                # only continue if ego is author of pub
                if (lastname_ego %in% pubs[[pub]]) {
                  aut_pot <- which.max(pubs[[pub]] %in% lastname_ego)
                  # only continue if ego is first author of pub
                  if (aut_pot == 1) {
                    # check all alters/co-authors
                    for (alter in 1:nrow(df_sel)) {
                      # which alter
                      lastname_alter <- df_sel$lastname[alter]
                      if (lastname_alter %in% pubs[[pub]]) {
                        networklist[[wave]][ego, alter] <- networklist[[wave]][ego, alter] + 1
                      }
                    }
                  }
                }
            }
        }
    }
    return(list(df = df_sel, network = networklist))
}

7.1 some testing

outputUU_sociology <- f_pubnets(affiliation = "UU")
str(outputUU_sociology)

#> List of 2
#>  $ df     :'data.frame': 62 obs. of  21 variables:
#>   ..$ id            : chr [1:62] "f84cb8" "ad5eeb" "5a5e57" "7c3ed2" ...
#>   ..$ uni           : chr [1:62] "UU" "UU" "UU" "UU" ...
#>   ..$ discipline    : chr [1:62] "sociology" "sociology" "sociology" "sociology" ...
#>   ..$ year          : num [1:62] 2022 2022 2022 2022 2022 ...
#>   ..$ name          : chr [1:62] "Ece Arat" "Marcel Van Assen" "Weverthon Barbosa Machado" "Vardan Barsegyan" ...
#>   ..$ affil1        : chr [1:62] "UU" "UU" "UU" "UU" ...
#>   ..$ affil2        : chr [1:62] "" "" "" "" ...
#>   ..$ position      : chr [1:62] "phd" "full_prof" "other" "other" ...
#>   ..$ np            : chr [1:62] "" "van" "" "" ...
#>   ..$ lastname      : chr [1:62] "arat" "assen" "machado" "barsegyan" ...
#>   ..$ firstname     : chr [1:62] "ece" "marcel" "weverthon" "vardan" ...
#>   ..$ ini           : chr [1:62] "" "" "" "" ...
#>   ..$ gender        : chr [1:62] "female" "male" "male" "male" ...
#>   ..$ gs_id         : chr [1:62] "_MW2-cgAAAAJ&hl" "uwPhxMcAAAAJ" "miJiVQcAAAAJ" "yh5pBBoAAAAJ" ...
#>   ..$ gs_name       : chr [1:62] "Ece Arat" "Marcel A.L.M. van Assen" "Weverthon Machado" "Vardan Barsegyan" ...
#>   ..$ gs_homepage   : chr [1:62] "https://www.uu.nl/medewerkers/EArat" NA "http://weverthon.com/" "https://www.wodc.nl/over-het-wodc/organisatie/medewerkers/vardan-barsegyan" ...
#>   ..$ gs_field      : chr [1:62] "Sociology" NA "Sociology" "Political Inequality" ...
#>   ..$ gs_i10_index  : num [1:62] 0 107 1 3 6 NA NA NA 76 0 ...
#>   ..$ gs_h_index    : num [1:62] 2 49 3 5 6 NA NA NA 35 2 ...
#>   ..$ gs_total_cites: num [1:62] 10 18428 33 66 229 ...
#>   ..$ gs_affiliation: chr [1:62] "Utrecht University" "Tilburg University, the Netherlands" "Postdoctoral researcher, Utrecht University" "The Research and Documentation Centre (WODC, The Hague, the Netherlands)" ...
#>  $ network:List of 2
#>   ..$ : num [1:62, 1:62] 0 0 0 0 0 0 0 0 0 0 ...
#>   ..$ : num [1:62, 1:62] 3 0 0 0 0 0 0 0 0 0 ...

head(outputUU_sociology[[1]])

#>       id uni discipline year                      name affil1 affil2  position  np  lastname
#> 1 f84cb8  UU  sociology 2022                  Ece Arat     UU              phd          arat
#> 2 ad5eeb  UU  sociology 2022          Marcel Van Assen     UU        full_prof van     assen
#> 3 5a5e57  UU  sociology 2022 Weverthon Barbosa Machado     UU            other       machado
#> 4 7c3ed2  UU  sociology 2022          Vardan Barsegyan     UU            other     barsegyan
#> 5 944260  UU  sociology 2022               Rutger Blom     UU            other          blom
#> 6 6c23fc  UU  sociology 2022                  Lute Bos     UU            other           bos
#>   firstname ini gender           gs_id                 gs_name
#> 1       ece     female _MW2-cgAAAAJ&hl                Ece Arat
#> 2    marcel       male    uwPhxMcAAAAJ Marcel A.L.M. van Assen
#> 3 weverthon       male    miJiVQcAAAAJ       Weverthon Machado
#> 4    vardan       male    yh5pBBoAAAAJ        Vardan Barsegyan
#> 5    rutger       male    RNktFGMAAAAJ             Rutger Blom
#> 6      lute       male                                    <NA>
#>                                                                  gs_homepage             gs_field
#> 1                                        https://www.uu.nl/medewerkers/EArat            Sociology
#> 2                                                                       <NA>                 <NA>
#> 3                                                      http://weverthon.com/            Sociology
#> 4 https://www.wodc.nl/over-het-wodc/organisatie/medewerkers/vardan-barsegyan Political Inequality
#> 5                                                                       <NA>                 <NA>
#> 6                                                                       <NA>                 <NA>
#>   gs_i10_index gs_h_index gs_total_cites
#> 1            0          2             10
#> 2          107         49          18428
#> 3            1          3             33
#> 4            3          5             66
#> 5            6          6            229
#> 6           NA         NA             NA
#>                                                             gs_affiliation
#> 1                                                       Utrecht University
#> 2                                      Tilburg University, the Netherlands
#> 3                              Postdoctoral researcher, Utrecht University
#> 4 The Research and Documentation Centre (WODC, The Hague, the Netherlands)
#> 5                              Postdoctoral researcher, Utrecht University
#> 6                                                                     <NA>

# head(outputUU_sociology[[2]])

It seems to work.

Assignment 4:
4a: Have a look at the networks. Could you describe the network? Dyad_census, triad_census? etc. 4b: What do you think/make of the evolution dynamics? Is there stability/change? Could you calculate the Jaccard Index?
4c: Define the relation/tie differently (see above for suggestions) and adapt the f_pubnets function so it can spit out different type of networks.

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