I got a top cited article! What does that mean?!?

December 19, 2014

Yesterday the Research Excellence Framework results were published, and it was therefore a nice coincidence to be notified by Springer yesterday that my paper is one of the top cited papers in Journal of Archaeological Method and Theory of 2013/2014. You can see it on this picture:


I am really happy and grateful about this. However, it did make me wonder what it means in numbers to have a top cited article. The answer is rather sobering: not much! In this blog post I will have a little look around citation land, and share some take-home messages about citation and impact in archaeology with you. Read on until the end, and you might find a call for revolution in the academic publishing world! 🙂

The source mentioned is ISI/Thomson Reuters database, and luckily I can access their metrics through Web of Science. A quick search revealed this paper has 8 citations on Web of Science (all databases), see the figure below:


That’s a sobering eyeopener! Especially considering one of these 8 citations is by a paper I wrote myself. This tells me quite a lot about the impact of the Journal of Archaeological Method and Theory, about the bit of archaeology that I am specialised in, and about that part of archaeologists’ citation behaviour represented by Web of Science.

Let’s start by that last one. Web of Science only indexes publications (mainly journals) with a long and consistent editorial board and publication history, focusing almost exclusively on English as the language of science. It defends this policy by stating the fact that the majority of all citations (about 60% or so) cite papers in a minority of journals (I believe about 20%, but don’t cite me on this). So there’s a clear tendency here to include high impact publications. Archaeology does not have many journals of high impact with a long tradition and a stable editorial history, whilst English is definitely NOT the only language of academic archaeology which is mainly due to the need to publish excavation reports in the local language. From my citation network analysis work I get the impression that less than half of all citations are included in Web of Science.

Why do I know that? Well let’s compare my 8 citation in Web of Science with how many this paper got according to Google Scholar:

jamt3So according to Google Scholar this paper was cited 16 times. Now Google Scholar does not care so much about the language or format of publication, so a much larger number of publications is indexed. But these citations also include those that are usually not included in any impact scores, such as citations mentioned on presentation slides or poster uploaded to the internet.

Take-home message number 1: check the citations to your paper on multiple citation databases before bragging about your impact (Web of Science, Google Scholar, Scopus).

What about the Journal of Archaeological Method and Theory? It is not the highest rated journal in archaeology, but I do think it’s up there in the top ten or so. But the top ten of what? Journals are usually ranked by their impact factor, which is the measure introduced by the Institute for Scientific Information using the data you can access through Web of Science. It represents the average number of citations in the last few years per paper in a journal. Here some Impact Factor results of the Journal of Archaeological Method and Theory:


In 2013 ISI gave it an impact factor of 1.389 which ranked it 18th in Anthropology, just below Antiquity and just above American Antiquity. These rankings are published yearly by ISI as the Journal Citation Reports. But there are more measures than just the Impact Factor. Google Scholar uses the h5 index to rank journals in disciplines: “the h5 index is the h-index for articles published in the last 5 complete years. It is the largest number h such that h articles published in 2009-2013 have at least h citations each”. In the category of Archaeology the Journal of Archaeological Method and Theory has an h5 index of 13 and ranks 15th: lower than American Antiquity and dwarfed by the scores of Journal of Archaeological Science (38) and Antiquity (21).

These measures of impact give you an idea of the number of citations on average a paper in a journal receives. This is not solely a result of a paper’s own merit or infamy. It should at least in part be seen as an effect of the journal itself being widely read, so papers published in well-known journals attract more citations because they adopt the visibility of the journal they are published in.

But citation practices differ greatly between disciplines. A quantitative measure of impact might therefore not be particularly relevant for all disciplines. For the humanities a more qualitative interpretation of impact is available: the European Reference Index for the Humanities. The site was down when I wrote this blog post, but the idea is simple. It gives a journal one of three ratings: of importance to a subdiscipline, of national importance for a discipline, of international importance for a discipline. But essentially this is just a low level classification based on a quantification of who publishes, cites, and reads each journal.

Take-home message number 2: impact is relative. Compare multiple measures as presented by multiple institutions. Visibility to your subdiscipline is more important than overall visibility/impact.

So my paper might not be cited by many, and it might not be published in the highest impact journal, but it is a piece of work I am pretty pleased with and it seems to reach the few people around the world who have the same niche interests I have. Having many citations according to ISI in my discipline really does not mean much. Way more impressive is the number of views and downloads this paper gets on sites like Academia.edu. We publish our work because we want to share it with those who are interested, and we want to provoke discussion with the final aim to advance human knowledge. Who cares about high citation counts? Just make sure your paper is out there, freely available, actively promote it, send it to those who might be interested in discussing it with you. That’s what you want, not a high impact factor. All these numbers, and especially the Research Excellence Framework, make us forget sometimes that it is science we are doing.

(PS: as a young academic I realize my own career will be enhanced by playing this numbers game. I am sure it will, for now. But I also think things are changing with resources like Academia.edu, which will hopefully push entities with empty prestige like Science and Nature off their pedestals. Scientific quality control is not guaranteed by prestigious publishers, and there are other models of publishing that allow us to debunk bullshit science and keep the good bits)

Special networky issue Archaeological Review Cambridge

April 29, 2014

arcNetworks are so hot right now in archaeology! I know of three archaeological journals publishing special issues on the topic very soon (will reveal this to you in later posts). Archaeological Review of Cambridge is the first of these to appear with a special issue titled ‘Social Network Perspectives in Archaeology’, edited by Kathrin Felder and Sarah Evans. The issue includes an editorial, a number of interesting papers, a reflective piece by Carl Knappett and some book reviews. I also published a paper in it titled ‘The roots and shoots of archaeological network analysis: A citation analysis and review of the archaeological use of formal network methods’. I will be introducing some pieces of this paper in future posts. For now, here is the contents of the special issue:

Social Network Perspectives in Archaeology
Issue 29.1, April 2014

Theme Editors: Sarah Evans and Kathrin Felder

Making the connection: Changing perspectives on social networks
Sarah Evans and Kathrin Felder

The roots and shoots of archaeological network analysis: A citation analysis and review of the archaeological use of formal network methods
Tom Brughmans

Population genetics and the investigation of past human interactions
Hayley Dunn

Eruptions and ruptures — a social network perspective on vulnerability and impact of the Laacher See eruption (c. 13,000 BP) on Late Glacial hunter-gatherers in northern Europe
Felix Riede

Expanding social networks through ritual deposition: A case study from the Lower Mississippi Valley
Erin Nelson and Megan Kassabaum

‘Extending the self ’ through material culture: Private letters and personal relationships in second-century AD Egypt
Jo Stoner

Play-things and the origins of online networks: Virtual material culture in multiplayer games
Angus Mol

The network approach: Tool or paradigm?
Francesca Fulminante

What are social network perspectives in archaeology?
Carl Knappett

Book Reviews
Edited by Mat Dalton

Computational Approaches to Archaeological Spaces
Edited by Andrew Bevan and Mark Lake Beaudry and Travis G. Parno
Reviewed by Peter Alfano

Cities and the Shaping of Memory in the Ancient Near East
By Ömür Harmanşah
Reviewed by Georgia Marina Andreou

The Oxford Handbook of the Archaeology of Death and Burial
Edited by Sarah Tarlow and Liv Nilsson Stutz
Reviewed by Michaela Binder

Network Analysis in Archaeology: New Approaches to Regional Interaction
Edited by Carl Knappett
Reviewed by Beatrijs G. de Groot

The Origins and Spread of Domestic Animals in Southwest Asia and Europe
Edited by Sue Colledge, James Connolly, Keith Dobney, Katie Manning and Stephen Shennan
Reviewed by Sarah Elliott

The Archaeology of Kinship
By Bradley E. Ensor
Reviewed by Philipp Y. Kao

Matters of Scale: Processes and Courses of Events in the Past and the Present
Edited by Nanouschka M. Burström and Fredrik Fahlander
Reviewed by Hannah L. McBeth

Cultural Heritage and the Challenge of Sustainability
By Diane Barthel-Bouchier
Reviewed by Belinda C. Mollard

The 48th IIPP Annual Conference on the Veneto Region, held in Padua on 5–9 November 2013
Reviewed by Elisa Perego

Humans and the Environment: New Archaeological Perspectives for the Twenty-first Century
Edited by Matthew I.J. Davies and Freda Nkirote M’Mbogori
Reviewed by Rachel Swallow

Citation analysis paper published in LLC

August 6, 2013

llc262coverIt took a while, but it’s finally published! My citation network analysis of archaeological literature can now be found in Literary and Linguistic Computing, the Digital Humanities journal. The paper looks at how archaeologists that used formal network techniques cited each other, and it tries to trace where they got their ideas from. To do this I use citation network analysis techniques developed in a field called Bibliometrics. It doesn’t sound particularly sexy, but I think it’s pretty cool stuff. Academic papers have long lists of references they cite, which can be considered a formal expression of where they  got their ideas from, or what they were influenced by. Each one of those papers can be considered a point or node in a network. An arrow is drawn between two papers if one cites the other. This creates a pretty web of citations when done for 10 papers, but it creates a complex messy spaghetti monster when done for more than 30,000 papers, as I illustrate in my paper. So for this reason we use network techniques to tackle such massive datasets and say something interesting about them.

Over the coming weeks I will write blog posts about some of the more interesting findings of this work. But do have a look at the published paper. If you have access to LLC then download it here. If not then you can find a link on my bibliography page or you can download it on Scribd.

Connected Island: Citation Network Analysis

February 18, 2013

In two previous blogposts (1, 2) I introduced the amazing Connected Island project Iza and I have been working on recently. This third blogpost about the Connected Island project will introduce our method for analysing publications and their citations. We will briefly discuss how citation network analysis works and the issues surrounding its applications. Finally, we will look at the very first results of this project: an analysis of publications about the Middle and Lower Palaeolithic in Hungary.

Hungarian Houses of Parliament

Hungarian Houses of Parliament

Citation network analysis

Recently, a wider availability of powerful computational resources, bibliometric software (e.g. HISTCITE; PAJEK; PUBLISH OR PERISH) and large bibliographic datasets in the sciences as well as the humanities resulted in significant progress in the analysis of citation networks in which vertices represent publications and a directed edge (or arc) between two vertices indicates a citation (Eom and Fortunato, 2011).

The foundations of citation network analysis were laid by Garfield et al. (1964) and the application of graph theory for citation network analysis was subsequently explored by Garner (1967). Despite this long tradition, its use in an archaeological context has not yet been thoroughly explored. In a number of studies researchers used simple counts of citations or other bibliometric data to track trends in the archaeological sciences and compare the impact and evolution of archaeological journals (e.g. Butzer, 2009; Marriner, 2009; Rehren et al., 2008; Rosenswig, 2005; Sterud, 1978), or to evaluate the impact of gender differentiation in archaeology (e.g. Beaudry and White, 1994; Hutson, 2002; 2006; Victor and Beaudry, 1992).

Citation network analyses in the Arts and Humanities are rare (Leydesdorff et al., 2011). The main reason for this is that the available citation databases for the Arts and Humanities (in particular the Institute for Scientific Information’s Arts and Humanities Citation Index) have significant limitations (Nederhof, 2006): books were until recently not indexed and publications in languages other than English are rare. However, monographs (rather than peer-reviewed journal articles) are often the dominant format of cited sources in the Humanities. Disciplines in the Arts and Humanities also show very different citation patterns and should therefore be considered separately (Knievel and Kellsey 2005). Despite these shortcomings citation analyses in the Arts and Humanities should not be discarded out of hand as it can still provide an alternative look at scientific practice through large aggregated datasets as long as the nature of the datasets and their limitations are thoroughly understood.

We came across some of these obstacles very early on during data collection for this project. Existing citation databases, like Web of Knowledge, contained only a fraction of the publications we were interested in. Those that are indexed in this resource are mostly written in English by Western European researchers (with a few exceptions) and it only rarely includes publications in Hungarian, Polish, Czech, Slovakian, or Russian. Manual data collection was therefore necessary.

A first test: the Lower and Middle Palaeolithic in Hungary

As a test-case we explored a small part of the project’s dataset, containing the 31 synthetic publications about the Lower and Middle Palaeolithic in Hungary we found in Budapest’s libraries. This collection of publications was written by nine Hungarian archaeologists between 1945 and 1990. This case-study aims to explore the citation patterns between them.

Chronological plot of citation network of Hungarian Palaeolithic researchers. Nodes are publications and directed lines are citations. Colours reflect publication language.

Chronological plot of citation network of Hungarian Palaeolithic researchers. Nodes are publications and directed lines are citations. Colours reflect publication language.

One would expect the older publications to be the most prominent since these had the time to accumulate the largest number of citations, and the results do show this process to some extent. Using the input domain measure (de Nooy et al., 2005: p. 193) we found that a few publications from the 50’s and early 60’s can be connected to by a larger number of nodes than any of the publications from the late 60’s and later, which indicates that these few publications influenced (directly or indirectly) the largest number of other publications. All of these publications with a high input domain were in fact written by a single author László Vértes who, although being very often cited by his colleagues, is guilty of quite a bit of self-citation as well. Although self-citation is common in academia and completely understandable (one always builds on one’s previous research), we needed to evaluate to what extent this affects the analytical techniques used. In this case the input domain seems to reflect largely the citation behaviour of one scholar who was extremely active throughout several decades.
Input domain score of publications: the number of publications that can be connected to a certain publication via a sequence of citations. This reflects the potential field of influence of a publication.

Input domain score of publications: the number of publications that can be connected to a certain publication via a sequence of citations. This reflects the potential field of influence of a publication.

Another way of evaluating the relative prominence of old and more recent publications is to look at the number of citations they received. It is interesting to note that the oldest as well as the recent publications receive a relatively small number of citations compared to a few publications from the mid- to late-60‘s. One of these is a monograph edited by Vértes on one of the most important Middle Palaeolithic sites in Hungary, Tata, which also received a high input domain score. The second highly cited publication was a book about the Middle Palaeolithic in Hungary also written by Vértes. The third most frequently cited work is a monograph about another prominent Middle Palaeolithic site, Érd, written by Veronika Gábori-Csánk.

In citation network analysis authoritative sources are often defined as publications that receive a high number of citations and particularly from so-called hubs. Hubs are defined as publications that cite a lot of other works especially authorities. Given these definitions we can identify the site monographs of Tata and Érd as well as the second highly cited book by Vértes as such authorities. The hubs in this network are three publications by the same authors: Miklos Gábori. All three of these publications are reviews of the Hungarian Palaeolithic and due to their very nature will include a lot of references, especially to key site reports.

The above measures very much over-emphasize the most cited publications and the work of the most active authors. We should note, however, that six works in this citation network are not cited or do not cite any others. These include publications from the 60’s by Vértes and Gabori, a few publications from the 50’s that seem to have been ignored by all those who followed, and the most recent publications from 1988 and 1990 that could not have been cited by others in this network.

Language of Publication

On the basis of the small sample of publications gathered in Budapest we can say that the widely held assumption that archaeological data from Central Europe was published in local languages is incorrect (Table 2). At least half, if not more, of Central European archaeology publications from this period were published in German, French or English alongside the national language. The image that all countries under the influence of the former Soviet Union published in Russian is incorrect.

Hungarian researchers in the case study, number of publications per language, and publishing date of publications included in the case study.

Hungarian researchers in the case study, number of publications per language, and publishing date of publications included in the case study.


We can conclude that although the effects of self-citation were definitely felt in this analysis, especially by those authors of whom we included multiple publications like Vértes or Gábori-Csánk, there are a number of publications that can be considered most pivotal in Hungarian Palaeolithic studies. These include the site reports of Tata and Érd.

Contrary to popular believe, Hungarian authors rarely published in their own language. Especially key site reports and synthetic works were written in these foreign languages, making them accessible to Western European archaeologists.

This blog post has explored the citation behaviour within a subset of the project’s dataset, and has concluded that Hungarian Palaeolithic archaeologists cited Central European and famous Western European scholars almost equally. Publications were almost always written in English, French or German, in addition to Hungarian, making most of them accessible to Western European archaeologists. But did the latter build on the work done by their Hungarian colleagues to improve their understanding of the European Lower and Middle Palaeolithic? Future work in this project will focus on the interactions between Western and Central European researchers.


Beaudry, M., & White, J. 1994. Cowgirls with the Blues? A Study of Women’s Publication and the Citation of Women’s Work in Historical Archaeology. In C. Claassen (ed) Women in Archaeology, 138–158. Philadelphia: University of Pennsylvania Press.

Butzer, K.W. 2009. Evolution of an interdisciplinary enterprise: the Journal of Archaeological Science at 35years. Journal of Archaeological Science 36(9): p.1842–1846.

Eom, Y.-H., & Fortunato, S. 2011. Characterizing and Modeling Citation Dynamics M. Perc (ed). PLoS ONE 6(9): p.e24926.

Garfield, E., Irving, H.S., & Richard, J.T. 1964. The use of citation data in writing the history of science. Philadelphia: Institute for scientific information.

Garner, R. 1967. A computer-oriented graph theoretic analysis of citation index structures. In B. Flood (ed) Three drexel information science research studies, 3–46. Philadelphia: Drexel press.

Hutson, S. 2002. Gendered citation practices in American Antiquity and other archaeology journals. American antiquity 67(2): p.331–342.

Hutson, S.R. 2006. Self-Citation in Archaeology: Age, Gender, Prestige, and the Self. Journal of Archaeological Method and Theory 13(1): p.1–18.

Knievel, J.E., & Kellsey, C. 2005. Citation analysis for collection development: a comparative study of eight humanities fields. The Library Quarterly 75(2): p.142–168.

Leydesdorff, L., Hammarfelt, B., & Salah, A. 2011. The structure of the Arts & Humanities Citation Index: A mapping on the basis of aggregated citations among 1,157 journals. Journal of the American Society for Information Science and Technology 62(12): p.2414–2426.

Marriner, N. 2009. Currents and trends in the archaeological sciences. Journal of Archaeological Science 36(12): p.2811–2815.

Nederhof, A. 2006. Bibliometric monitoring of research performance in the Social Sciences and the Humanities : a review. Scientometrics 66(1): p.81–100.

Nooy, W. de, Mrvar, A., & Batagelj, V. 2005. Exploratory social network analysis with Pajek. Cambridge ; New York: Cambridge University Press.

Rehren, T., Grattan, J., & Klein, R. 2008. Going strong, and growing. Journal of Archaeological Science 35: p.94305.

Rosenswig, R. 2005. A tale of two antiquities: Evolving editorial policies of the SAA journals. The SAA Archeological Record 5(1): p.15–21.

Sterud, E. 1978. Changing Aims of Americanist Archaeology: A Citations Analysis of American Antiquity. 1946-1975. American Antiquity 43(2): p.294–302.

Victor, K., & Beaudry, M. 1992. Women’s Participation in American Prehistoric and Historic Archaeology: A Comparative Look at the Journals American Antiquity and Historical Archaeology. In C. Claassen (ed) Exploring Gender through Archaeology, 11–22. Madison, Wisconsin: Prehistory Press.

‘A Connected Island?’: measuring academic influence

January 17, 2013

By Iza Romanowska and Tom Brughmans

This second blog post about the Connect Island project, funded by a sotonDH small award, discusses the relative influence of Central European Palaeolithic researchers using the H-index measure.

hindex all

Figure 1: H-index scores of Central European Palaeolithic researchers (left) versus Iron Age (right) researchers.

It has been claimed that Central European archaeologists specializing in Stone Age studies are quite well-known in the West compared to their colleagues leading research in later epochs. To test this anecdotal supposition we analysed the H-index of Central European Palaeolithic researchers.

The H-index (Hirsch 2005) is a measure of an author’s academic impact that takes into account both the number of papers published by the author and the number of citations to these papers (Bornmann and Daniel 2005; 2007). Its main advantage is that it balances the effects of a small number of high hitting papers and a large number of rarely cited publications. Neither a researcher with a one-hit-wonder paper, nor one producing hundreds of mediocre publications will score high. The H-index therefore favours enduring performance both in terms of quality and quantity. We used publications and citations recorded in Google Scholar as it covers a higher number of publications than ISI Web of Knowledge, especially for the fields of Social Sciences and Arts and Humanities (Kousha and Thelwall 2008). In contrast to ISI Web of Knowledge, however, Google’s bibliographic indexing is automated and not routinely manually edited by Google staff making it prone to inconsistencies and duplication. We noticed that the H-index results for archaeologists were unrealistically low when only taking publications in Web of Knowledge into account, and Google Scholar was therefore considered the lesser of two evils.

To provide a benchmark, we compared the results with a large sample of Central European Iron Age researchers. The Central European Iron Age is quite extensive, well-studied and some of its main proponents are well-known internationally. Arguably, the fact that we are using Iron Age researchers for this benchmark is irrelevant, any sub-discipline within archaeology would have done the job. In order for the anecdotal statement we are trying to test to be true, however, the H-index scores of the Palaeolithic researchers should be close to or higher than the Iron Age researchers’.

The results strongly confirm the intuitive observation (see Table 1 and Figure 1). Compared to a test sample of Iron Age specialists, Central European Palaeolithic researchers have been quoted more extensively and their papers were more influential abroad (as reflected in Google Scholar), indicating that they had a higher direct impact (as measured by the H-index) on the discipline globally.

Palaeolithic researchers   Iron Age researchers  
Karel Absolon 9 Kazimierz Bielenin 4
Viola Dobosi 5 Anna Bitner-Wróblewska 2
Boleslaw Ginter 7 Éva Bónis 3
Jan Fridrich 4 Jaroslav Böhm 6
 Bohuslav Klíma 10 Miloš Čižmář 3
Michal Kobusiewicz 8 Jana Čižmářová 1
Janusz Krzysztof Kozlowski 10 Sylwester Czopek 2
Stefan Kozlowski 9 Petr Drda 4
Gábori Miklós 5 Jan Filip 11
Martin Oliva 9 Kazimierz Godlowski 7
Romuald Schild 22 Eszter Istvánovits 2
Josef Skutil 5 Libuše Jansová 3
Jiří Svoboda 14 Fitz Jenő 9
Karel Valoch 14 Piotr Kaczanowski 5
László Vértes 11 Andrzej Kokowski 3
Jerzy Kmieciński 4
Valéria Kulcsár 2
Karel Ludikovský 1
Henryk Machajewski 2
 Renata Madyda-Legutko 3
Magdalena Mączyńska 3
Jiří Meduna 4
Szabó Miklós 5
Karla Motyková-Šneidrová 2
Jerzy Okulicz-Kozaryn 2
Emanuel Šimek 4
Jaroslav Tejral 8
Andrea Vaday 3
Natalie Venclová 5
Jiří Waldhauser 3
Ryszard Wołągiewicz 2
Table 1: all Palaeolithic and Iron Age researchers included in the analysis with their H-index scores.

The Matthew effect?

We suspect that we are dealing here with a good example of the “Matthew effect” in science. Coined by Robert K. Merton (1968), the term refers to a passage from the Gospel of Matthew: “For to all those who have, more will be given, and they will have an abundance; but from those who have nothing, even what they have will be taken away.” – Matthew 25:29.

In simple terms it can be referred to as the “rich get richer” effect. Applied to academia it describes the phenomenon of more established, better-known scholars receiving disproportionately more credit than their lesser-known colleagues for equal or even smaller contributions to the research. Thus, they are more likely to spread their results wider and to have a higher impact on the discipline. Lower Palaeolithic archaeology had an additional boost when it came to creating a strong Matthew effect. The few irregularly distributed Lower Palaeolithic sites could be studied and published by only a handful of specialists. As a result, only a limited number of archaeologists were drawn into Palaeolithic studies and those who did were exempt from the fierce competition that their colleagues working on later epochs faced.

This also meant that invitations to conferences, scientific collaboration and co-authoring would be shared within a smaller cluster of scholars creating a self-propelling positive feedback loop and strengthening the natural Matthew effect. Combined with the nature of Palaeolithic data which is of global relevance and the high demand for Palaeolithic researchers in the second half of the 20th century, this could have contributed to a better recognition of Central European Palaeolithic researchers in the West, giving them more opportunities to collaborate, publish and spread their results in the international research community. Such a process could account for the higher H-index compared to their colleagues specializing in later epochs.


Bornmann, L., H.-D. Daniel. 2005. “Does the h-index for ranking of scientists really work?” Scientometrics 65 (3): 391-392. doi:10.1007/s11192-005-0281-4.
Bornmann, L., H.-D. Daniel. 2007. “What do we know about the h-index?” Journal of the American Society for Information Science and Technology 58 (9): 1381-1385. doi:10.1002/asi.20609.
Hirsch, J. E. 2005. “An index to quantify an individual’s scientific research output.” Proceedings of the National Academy of Sciences of the United States of America 102 (46) (November 15): 16569-16572. doi:10.1073/pnas.0507655102.
Kousha, K., M. Thelwall. 2007. “Sources of Google Scholar citations outside the Science Citation Index: A comparison between four science disciplines.” Scientometrics 74 (2): 273-294. doi:10.1007/s11192-008-0217-x.
Merton, Robert K. 1968. “The Matthew Effect in Science.” Advancement of Science 159 (3810): 56-63.
Merton, Robert K. 1988. “The Matthew Effect in Science II. Cumulative Advantage and the Symbolism of Intellectual Property.” Sociology. The Journal of the British Sociological Association 159: 606-623.

Happy New Year! and CAAUK

January 15, 2013

Screen shot 2013-01-15 at 17.10.32Happy New Year all! There are a couple of events in 2013 I am really looking forward to, including the CAA conference in Perth and the SAAs in Hawaii, more about those later. The first conference of the year for me will be CAAUK in London, on 22-23 February. The programme sounds great, with a keynote by Mark Lake discussing the special issue of World Archaeology he recently edited on Open Archaeology. Registration is now open but almost full, so hurry up if you wanna be part of it!

I will present a poster on a project Iza Romanowska and I have set up: ‘A Connected Island?: how the Iron Curtain affected archaeologists’. We are touring Central Europe’s libraries for this project, collecting publications by Central European Palaeolithic archaeologists. We hope to be able to evaluate the interactions between Western and Central European archaeologists, and we hope our methodology of citation network analysis will help us do this. More about the project in later posts! The poster will be presented by Iza at the Unravelling the Palaeolithic conference in Cambridge this weekend. Here is the abstract:

‘A Connected Island?’: How the Iron Curtain affected Palaeolithic Archaeologists in Central Europe

Iza Romanowska (Centre for the Archaeology of Human Origins, University of Southampton)
Tom Brughmans (Archaeological Computing Research Group, University of Southampton)

After the Second World War the Iron Curtain sliced through the very centre of Europe. The Soviet regime introduced a new structure to the academic institutions in countries like Poland, Hungary and former Czechoslovakia, including restrictions on contacts with the Western world and ideological pressure. How did this situation affect researchers on both sides? Was Central European Academia really isolated from western influences?

It is difficult to quantitatively determine to what degree these limitations affected archaeologists. The project team argues that citation data might allow (at least in part) for such a quantitative evaluation. Citations are like handy formal proxies for tracing lines of knowledge dissemination and academic influence, obviously not fully representative for these very complex processes, but well suited to quantify the ‘awareness’ of other peoples’ research.

The project will initially focus on the Lower and Middle Palaeolithic of Poland, former Czechoslovakia and Hungary. Citations have been extracted from publications of a synthetic nature (i.e. not field reports) and a citation network analysis has been performed on that data. Our preliminary results indicate that a lot of common presumptions regarding the research behind the Iron Curtain, like the dominance of Russian or national languages in Academic writing, are in fact false.

Citation analysis: winner takes all

November 7, 2012

A small group of papers (1%) often gets a disproportional amount of attention and citations (17%). This pattern has been identified a long time ago (have a look at the Web of Science selection procedure as an example of this trend). A short correspondence by Barabási, Song and Wang published recently in Nature revealed that this pattern only emerges after some time and that those top 1% of papers are not necessarily cited a lot immediately after they emerge. The authors argue that this pattern might be a result of our changing reading habits now that academic publications are so abundant, easily searchable and as a result easily accessible: “Researchers increasingly rely on crowd sourcing to discover relevant work, a process that favours the leading papers at the expense of the remaining 99%”.

Read the full correspondence on the Nature website.