-
Herb, U.; Beucke, D.: ¬Die Zukunft der Impact-Messung : Social Media, Nutzung und Zitate im World Wide Web (2013)
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- Content
- Vgl. unter: https://www.leibniz-science20.de%2Fforschung%2Fprojekte%2Faltmetrics-in-verschiedenen-wissenschaftsdisziplinen%2F&ei=2jTgVaaXGcK4Udj1qdgB&usg=AFQjCNFOPdONj4RKBDf9YDJOLuz3lkGYlg&sig2=5YI3KWIGxBmk5_kv0P_8iQ.
-
Burrell, Q.L.: Predicting future citation behavior (2003)
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- Abstract
- In this article we further develop the theory for a stochastic model for the citation process in the presence of obsolescence to predict the future citation pattern of individual papers in a collection. More precisely, we investigate the conditional distribution-and its mean- of the number of citations to a paper after time t, given the number of citations it has received up to time t. In an important parametric case it is shown that the expected number of future citations is a linear function of the current number, this being interpretable as an example of a success-breeds-success phenomenon.
- Date
- 29. 3.2003 19:22:48
-
Li, T.-C.: Reference sources in periodicals : research note (1995)
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- Abstract
- Presents a list of 53 periodicals in 22 subject fields which regularly provide bibliographies of theses, research in progress and patents in their particular subject field. The fields of business, economics, history and literature have most periodical listings of dissertations and theses. Also lists 63 periodicals in 25 sub-disciplines which provide rankings or ratings. Rankings and ratings information predominates in the fields of business, sports and games, finance and banking, and library and information science
-
Thelwall, M.; Ruschenburg, T.: Grundlagen und Forschungsfelder der Webometrie (2006)
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- Date
- 4.12.2006 12:12:22
-
Althouse, B.M.; West, J.D.; Bergstrom, C.T.; Bergstrom, T.: Differences in impact factor across fields and over time (2009)
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- Date
- 23. 2.2009 18:22:28
-
¬Die deutsche Zeitschrift für Dokumentation, Informationswissenschaft und Informationspraxis von 1950 bis 2011 : eine vorläufige Bilanz in vier Abschnitten (2012)
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- Date
- 22. 7.2012 19:35:26
- Footnote
- Besteht aus 4 Teilen: Teil 1: Eden, D., A. Arndt, A. Hoffer, T. Raschke u. P. Schön: Die Nachrichten für Dokumentation in den Jahren 1950 bis 1962 (S.159-163). Teil 2: Brose, M., E. durst, D. Nitzsche, D. Veckenstedt u. R. Wein: Statistische Untersuchung der Fachzeitschrift "Nachrichten für Dokumentation" (NfD) 1963-1975 (S.164-170). Teil 3: Bösel, J., G. Ebert, P. Garz,, M. Iwanow u. B. Russ: Methoden und Ergebnisse einer statistischen Auswertung der Fachzeitschrift "Nachrichten für Dokumentation" (NfD) 1976 bis 1988 (S.171-174). Teil 4: Engelage, H., S. Jansen, R. Mertins, K. Redel u. S. Ring: Statistische Untersuchung der Fachzeitschrift "Nachrichten für Dokumentation" (NfD) / "Information. Wissenschaft & Praxis" (IWP) 1989-2011 (S.164-170).
-
Huang, M.-H.; Huang, W.-T.; Chang, C.-C.; Chen, D. Z.; Lin, C.-P.: The greater scattering phenomenon beyond Bradford's law in patent citation (2014)
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- Date
- 22. 8.2014 17:11:29
-
Ntuli, H.; Inglesi-Lotz, R.; Chang, T.; Pouris, A.: Does research output cause economic growth or vice versa? : evidence from 34 OECD countries (2015)
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- Date
- 8. 7.2015 22:00:42
-
Schubert, T.; Michels, C.: Placing articles in the large publisher nations : is there a "free lunch" in terms of higher impact? (2013)
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- Date
- 22. 3.2013 19:45:49
-
Ortega, J.L.: ¬The presence of academic journals on Twitter and its relationship with dissemination (tweets) and research impact (citations) (2017)
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- Abstract
- Purpose The purpose of this paper is to analyze the relationship between dissemination of research papers on Twitter and its influence on research impact. Design/methodology/approach Four types of journal Twitter accounts (journal, owner, publisher and no Twitter account) were defined to observe differences in the number of tweets and citations. In total, 4,176 articles from 350 journals were extracted from Plum Analytics. This altmetric provider tracks the number of tweets and citations for each paper. Student's t-test for two-paired samples was used to detect significant differences between each group of journals. Regression analysis was performed to detect which variables may influence the getting of tweets and citations. Findings The results show that journals with their own Twitter account obtain more tweets (46 percent) and citations (34 percent) than journals without a Twitter account. Followers is the variable that attracts more tweets (ß=0.47) and citations (ß=0.28) but the effect is small and the fit is not good for tweets (R2=0.46) and insignificant for citations (R2=0.18). Originality/value This is the first study that tests the performance of research journals on Twitter according to their handles, observing how the dissemination of content in this microblogging network influences the citation of their papers.
- Date
- 20. 1.2015 18:30:22
-
Egghe, L.: Untangling Herdan's law and Heaps' law : mathematical and informetric arguments (2007)
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- Abstract
- Herdan's law in linguistics and Heaps' law in information retrieval are different formulations of the same phenomenon. Stated briefly and in linguistic terms they state that vocabularies' sizes are concave increasing power laws of texts' sizes. This study investigates these laws from a purely mathematical and informetric point of view. A general informetric argument shows that the problem of proving these laws is, in fact, ill-posed. Using the more general terminology of sources and items, the author shows by presenting exact formulas from Lotkaian informetrics that the total number T of sources is not only a function of the total number A of items, but is also a function of several parameters (e.g., the parameters occurring in Lotka's law). Consequently, it is shown that a fixed T(or A) value can lead to different possible A (respectively, T) values. Limiting the T(A)-variability to increasing samples (e.g., in a text as done in linguistics) the author then shows, in a purely mathematical way, that for large sample sizes T~ A**phi, where phi is a constant, phi < 1 but close to 1, hence roughly, Heaps' or Herdan's law can be proved without using any linguistic or informetric argument. The author also shows that for smaller samples, a is not a constant but essentially decreases as confirmed by practical examples. Finally, an exact informetric argument on random sampling in the items shows that, in most cases, T= T(A) is a concavely increasing function, in accordance with practical examples.
-
Ye, F.Y.: ¬A theoretical approach to the unification of informetric models by wave-heat equations (2011)
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- Abstract
- A simple distribution function f(x, t)=p(x+q)**-ße**alpha*t obeys wave and heat equations, that constructs a theoretical approach to the unification of informetric models, with which we can unify all informetric laws. While its space-type distributions deduce naturally Lotka-type laws in size approaches and Zipf-type laws in rank approaches, its time-type distributions introduce the mechanism of Price-type and Brookes-type laws.
-
Burrell, Q.L.: "Type/Token-Taken" informetrics : Some comments and further examples (2003)
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- Abstract
- Egghe has propounded the notion of Type/Token-Taken (T/TT) informetrics. In this note we show how his ideas relate to ones that are already well known in informetrics and resolve some of the specific problems posed.
-
Egghe, L.; Ravichandra Rao, I.K.: ¬The influence of the broadness of a query of a topic on its h-index : models and examples of the h-index of n-grams (2008)
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- Abstract
- The article studies the influence of the query formulation of a topic on its h-index. In order to generate pure random sets of documents, we used N-grams (N variable) to measure this influence: strings of zeros, truncated at the end. The used databases are WoS and Scopus. The formula h=T**1/alpha, proved in Egghe and Rousseau (2006) where T is the number of retrieved documents and is Lotka's exponent, is confirmed being a concavely increasing function of T. We also give a formula for the relation between h and N the length of the N-gram: h=D10**(-N/alpha) where D is a constant, a convexly decreasing function, which is found in our experiments. Nonlinear regression on h=T**1/alpha gives an estimation of , which can then be used to estimate the h-index of the entire database (Web of Science [WoS] and Scopus): h=S**1/alpha, , where S is the total number of documents in the database.
-
Egghe, L.; Rousseau, R.: ¬The Hirsch index of a shifted Lotka function and its relation with the impact factor (2012)
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- Abstract
- Based on earlier results about the shifted Lotka function, we prove an implicit functional relation between the Hirsch index (h-index) and the total number of sources (T). It is shown that the corresponding function, h(T), is concavely increasing. Next, we construct an implicit relation between the h-index and the impact factor IF (an average number of items per source). The corresponding function h(IF) is increasing and we show that if the parameter C in the numerator of the shifted Lotka function is high, then the relation between the h-index and the impact factor is almost linear.
-
Chen, C.-M.: Classification of scientific networks using aggregated journal-journal citation relations in the Journal Citation Reports (2008)
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- Abstract
- I propose an approach to classifying scientific networks in terms of aggregated journal-journal citation relations of the ISI Journal Citation Reports using the affinity propagation method. This algorithm is applied to obtain the classification of SCI and SSCI journals by minimizing intracategory journal-journal (J-J) distances in the database, where distance between journals is calculated from the similarity of their annual citation patterns with a cutoff parameter, t, to restrain the maximal J-J distance. As demonstrated in the classification of SCI journals, classification of scientific networks with different resolution is possible by choosing proper values of t. Twenty journal categories in SCI are found to be stable despite a difference of an order of magnitude in t. In our classifications, the level of specificity of a category can be found by looking at its value of RJ (the average distance of members of a category to its representative journal), and relatedness of category members is implied by the value of DJ-J (the average DJ-J distance within a category). Our results are consistent with the ISI classification scheme, and the level of relatedness for most categories in our classification is higher than their counterpart in the ISI classification scheme.
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Rao, I.K.: ¬The distribution of scientific productivity and social change (1978)
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- Abstract
- Results in the literature concerning the probability that an author publishes r articles in time t are reexamined, and it is found that a negative binomial distribution bits scientific productivity data (by the chi-squared goodness-of-fit-test) better than many other distribution such as geometric, logarithmic, zeta, cumulative advantage, etc. It is shown analytically that the nagative binomial distribution describes a pattern of scientific productivity under the 'success-breeds-success' condition in a wide variety of social circumstances
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Burrell, Q.L.: Will this paper ever be cited? (2002)
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- Abstract
- A recently proposed stochastic model to describe the citation process in the presence of obsolescence is used to answer the question: If a paper has not been cited by time t after its publication, what is the probability that it will ever be cited?
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Marchant, T.: Score-based bibliometric rankings of authors (2009)
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Tscherteu, G.; Langreiter, C.: Explorative Netzwerkanalyse im Living Web (2009)
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- Source
- Social Semantic Web: Web 2.0, was nun? Hrsg.: A. Blumauer u. T. Pellegrini
