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Title:
Lastnosti biofizikalnih objav skozi čas : magistrsko delo
Authors:
ID
Gačević, Dino
(Author)
ID
Markovič, Rene
(Mentor)
More about this mentor...
Files:
MAG_Gacevic_Dino_2022.pdf
(3,24 MB)
MD5: 31C45D9692AF835096389C770463A51F
Language:
Slovenian
Work type:
Master's thesis/paper
Typology:
2.09 - Master's Thesis
Organization:
FNM - Faculty of Natural Sciences and Mathematics
Abstract:
V zadnjih letih beležimo porast števila strokovnih in znanstvenih objav, sočasno s tem pa tudi število novo nastalih, interdisciplinarnih področij. Sem uvrščamo tudi področje biofizike, izbrano za izhodiščno točko naše raziskave. V magistrskem delu smo najprej z uporabo podatkovnega rudarjenja iz spletne baze PubMed pridobili nabor za področje relevantnih člankov, nato pa pripravili splošni pregled od leta 1900 naprej. Ugotovili smo, da je število objavljenih člankov, povprečno število avtorjev na članek ter delež člankov s ključnimi besedami skozi leta naraščal. S podatki o revijah z največ objavljenimi članki ter najpogostejšimi ključnimi besedami smo ponazorili trende, ki odražajo postopen prehod naravnanosti v splošno fiziko do specializiranosti v področje biofizike. Enak trend smo potrdili še z najpogostejšimi n-grami skozi leta ter analizo MeSH deskriptorjev. Podrobneje smo predstavili tudi trende držav z največ objavami ter ugotovili, da so do leta 2020 prednjačile ZDA, po letu 2020 pa je vodilno mesto prevzela Kitajska. Ogledali smo si še medsebojno povezovanje avtorjev oz. držav, iz katerih ti prihajajo. Z delitvijo rezultatov v tri obdobja smo prikazali postopno krepitev medsebojnega povezovanja. Nalogo smo zaokrožili s prikazom razvoja in trendov področja biofizike na podlagi analize MeSH deskriptorjev. Rezultati so pokazali, da se velik delež terminov prenese v nova obdobja. Povprečno se pojavi 21 % novih ter pozabi 11 % vseh terminov. Z analizo ugotovljenih terminov se je izkazalo, da močno prevladuje termin »strunarji«, ki poudarja področje biologije, za področje fizike pa so se kot najpomembnejši termini izkazali »algoritmi«, »epidemiološke metode« ter »akustika«, nedavno pa tudi »avtomatizacija«.
Keywords:
podatkovno rudarjenje
,
analiza besedila
,
MeSH
,
kompleksne mreže
Place of publishing:
Maribor
Place of performance:
Maribor
Publisher:
[D. Gačević]
Year of publishing:
2022
Number of pages:
43 str.
PID:
20.500.12556/DKUM-83183
UDC:
53:004.89(043.2)
COBISS.SI-ID:
127501827
Publication date in DKUM:
28.10.2022
Views:
729
Downloads:
62
Metadata:
Categories:
FNM
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:
GAČEVIĆ, Dino, 2022,
Lastnosti biofizikalnih objav skozi čas : magistrsko delo
[online]. Master’s thesis. Maribor : D. Gačević. [Accessed 24 April 2025]. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=83183
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Licences
License:
CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:
http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:
The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:
26.09.2022
Secondary language
Language:
English
Title:
Characteristics of biophysical publications over time
Abstract:
Recent years have seen an increase in professional and scientific publications and a parallel rise in the number of newly emerging, interdisciplinary fields. That includes biophysics, chosen as the starting point for our research. Firstly we extracted a set of relevant articles from the PubMed online database using data mining and then prepared a general overview from 1900 onwards. We found that the number of articles published, the average number of authors per article, and the proportion of articles with keywords have increased over the years. Using data on the journals with the most published articles and the most frequent keywords, we have illustrated trends reflecting the gradual transition from a focus on general physics to a specialization in biophysics. We confirmed that also with the most frequent n-grams over the years and the analysis of MeSH descriptors. We also presented in more detail the trends of the countries with the most publications and found that the USA was the leading country up to 2020, with China taking the lead after 2020. We also looked at the interconnection between authors and their country of origin. By dividing the results into three periods, we have shown the gradual strengthening of interconnection. We rounded off the Master's thesis by displaying the development and trends in the field of biophysics based on the analysis of MeSH descriptors. It turns out that a majority of terms are carried over into new periods, with an average of 21% of new terms appearing and 11% of all terms disappearing. The analysis of the identified terms shows that the term "Chordata" is strongly dominating, highlighting the field of biology while »algorithms«, »epidemiological methods«, »acoustics«, and more recently »automation«, have emerged as the most eminent terms for the field of physics.
Keywords:
data mining
,
text analysis
,
MeSH
,
complex networks
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