-
Zitt, M.; Small, H.: Modifying the journal impact factor by fractional citation weighting : the audience factor (2008)
0.00
0.0030444188 = product of:
0.0060888375 = sum of:
0.0060888375 = product of:
0.012177675 = sum of:
0.012177675 = weight(_text_:a in 2363) [ClassicSimilarity], result of:
0.012177675 = score(doc=2363,freq=18.0), product of:
0.053105544 = queryWeight, product of:
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046056706 = queryNorm
0.22931081 = fieldWeight in 2363, product of:
4.2426405 = tf(freq=18.0), with freq of:
18.0 = termFreq=18.0
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046875 = fieldNorm(doc=2363)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- A new approach to the field normalization of the classical journal impact factor is introduced. This approach, called the audience factor, takes into consideration the citing propensity of journals for a given cited journal, specifically, the mean number of references of each citing journal, and fractionally weights the citations from those citing journals. Hence, the audience factor is a variant of a fractional citation-counting scheme, but computed on the citing journal rather than the citing article or disciplinary level, and, in contrast to other cited-side normalization strategies, is focused on the behavior of the citing entities. A comparison with standard journal impact factors from Thomson Reuters shows a more diverse representation of fields within various quintiles of impact, significant movement in rankings for a number of individual journals, but nevertheless a high overall correlation with standard impact factors.
- Type
- a
-
Small, H.: ¬A general framework for creating large scale maps of science in two or three dimensions : the SciViz system (1998)
0.00
0.0030255679 = product of:
0.0060511357 = sum of:
0.0060511357 = product of:
0.012102271 = sum of:
0.012102271 = weight(_text_:a in 1039) [ClassicSimilarity], result of:
0.012102271 = score(doc=1039,freq=10.0), product of:
0.053105544 = queryWeight, product of:
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046056706 = queryNorm
0.22789092 = fieldWeight in 1039, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.0625 = fieldNorm(doc=1039)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- Data visualization techniques have opened up new possibilities for science mapping. To exploit this opportunity new methods are needed to position tens of thousands of documents in a single coordinate space. Describes a general framework for achieving this goal involving hierarchical clustering, ordination of clusters, and the merging of ordinations into a common coordinate space. Presents the SciViz system as one particular implementation of this framework
- Type
- a
-
Small, H.; Sweeney, E.: Clustering the Science Citation Index using co-citations (1985)
0.00
0.00270615 = product of:
0.0054123 = sum of:
0.0054123 = product of:
0.0108246 = sum of:
0.0108246 = weight(_text_:a in 1064) [ClassicSimilarity], result of:
0.0108246 = score(doc=1064,freq=2.0), product of:
0.053105544 = queryWeight, product of:
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046056706 = queryNorm
0.20383182 = fieldWeight in 1064, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.125 = fieldNorm(doc=1064)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Type
- a
-
Small, H.: Update on science mapping : creating large document spaces (1997)
0.00
0.0020506454 = product of:
0.004101291 = sum of:
0.004101291 = product of:
0.008202582 = sum of:
0.008202582 = weight(_text_:a in 410) [ClassicSimilarity], result of:
0.008202582 = score(doc=410,freq=6.0), product of:
0.053105544 = queryWeight, product of:
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046056706 = queryNorm
0.1544581 = fieldWeight in 410, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.0546875 = fieldNorm(doc=410)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- Science mapping projects have been revived by the advent of virtual reality (VR) software capable of navigating large sysnthetic 3 dimensional spaces. Unlike the earlier mapping efforts aimed at creating simple maps at either a global or local level, the focus is now on creating large scale maps displaying many thousands of documents which can be input into the new VR systems. Presents a general framework for creating large scale document spaces as well as some new methods which perform some of the individual processing steps. The methods are designed primarily for citation data but could be applied to other types of data, including hypertext links
- Type
- a
-
Small, H.: Paradigms, citations, and maps of science : a personal history (2003)
0.00
0.0020296127 = product of:
0.0040592253 = sum of:
0.0040592253 = product of:
0.008118451 = sum of:
0.008118451 = weight(_text_:a in 1456) [ClassicSimilarity], result of:
0.008118451 = score(doc=1456,freq=8.0), product of:
0.053105544 = queryWeight, product of:
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046056706 = queryNorm
0.15287387 = fieldWeight in 1456, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046875 = fieldNorm(doc=1456)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- Can maps of science tell us anything about paradigms? The author reviews his earlier work an this question, including Kuhn's reaction to it. Kuhn's view of the role of bibliometrics differs substantially from the kinds of reinterpretations of paradigms that information scientists are currently advocating. But these reinterpretations are necessary if his theory will ever be empirically tested, and further progress is to be made in understanding the growth of scientific knowledge. A new Web tool is discussed that highlights rapidly changing specialties that may lead to new ways of monitoring revolutionary change in real time. It is suggested that revolutionary and normal science be seen as extremes an a continuum of rates of change rather than, as Kuhn originally asserted, as an all or none proposition.
- Type
- a
-
Boyack, K.W.; Small, H.; Klavans, R.: Improving the accuracy of co-citation clustering using full text (2013)
0.00
0.0020296127 = product of:
0.0040592253 = sum of:
0.0040592253 = product of:
0.008118451 = sum of:
0.008118451 = weight(_text_:a in 1036) [ClassicSimilarity], result of:
0.008118451 = score(doc=1036,freq=8.0), product of:
0.053105544 = queryWeight, product of:
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046056706 = queryNorm
0.15287387 = fieldWeight in 1036, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046875 = fieldNorm(doc=1036)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- Historically, co-citation models have been based only on bibliographic information. Full-text analysis offers the opportunity to significantly improve the quality of the signals upon which these co-citation models are based. In this work we study the effect of reference proximity on the accuracy of co-citation clusters. Using a corpus of 270,521 full text documents from 2007, we compare the results of traditional co-citation clustering using only the bibliographic information to results from co-citation clustering where proximity between reference pairs is factored into the pairwise relationships. We find that accounting for reference proximity from full text can increase the textual coherence (a measure of accuracy) of a co-citation cluster solution by up to 30% over the traditional approach based on bibliographic information.
- Type
- a
