The History and Meaning of the Journal Impact Factor
TL;DR: The journal impact factor was created to help select additional source journals and is based on the number of citations in the current year to items published in the previous 2 years, which allows for the inclusion of many small but influential journals.
Abstract: IFIRST MENTIONED THE IDEA OF AN IMPACT FACTOR IN Science in 1955. With support from the National Institutes of Health, the experimental Genetics Citation Index was published, and that led to the 1961 publication of the Science Citation Index. Irving H. Sher and I created the journal impact factor to help select additional source journals. To do this we simply re-sorted the author citation index into the journal citation index. From this simple exercise, we learned that initially a core group of large and highly cited journals needed to be covered in the new Science Citation Index (SCI). Consider that, in 2004, the Journal of Biological Chemistry published 6500 articles, whereas articles from the Proceedings of the National Academy of Sciences were cited more than 300 000 times that year. Smaller journals might not be selected if we rely solely on publication count, so we created the journal impact factor (JIF). The TABLE provides a selective list of journals ranked by impact factor for 2004. The Table also includes the total number of articles published in 2004, the total number of articles published in 2002 plus 2003 (the JIF denominator), the citations to everything published in 2002 plus 2003 (the JIF numerator), and the total citations in 2004 for all articles ever published in a given journal. Sorting by impact factor allows for the inclusion of many small (in terms of total number of articles published) but influential journals. Obviously, sorting by total citations or other provided data would result in a different ranking. The term “impact factor” has gradually evolved to describe both journal and author impact. Journal impact factors generally involve relatively large populations of articles and citations. Individual authors generally produce smaller numbers of articles, although some have published a phenomenal number. For example, transplant surgeon Tom Starzl has coauthored more than 2000 articles, while Carl Djerassi, inventor of the modern oral contraceptive, has published more than 1300. Even before the Journal Citation Reports (JCR) appeared, we sampled the 1969 SCI to create the first published ranking by impact factor. Today, the JCR includes every journal citation in more than 5000 journals—about 15 million citations from 1 million source items per year. The precision of impact factors is questionable, but reporting to 3 decimal places reduces the number of journals with the identical impact rank. However, it matters very little whether, for example, the impact of JAMA is quoted as 24.8 rather than 24.831. A journal’s impact factor is based on 2 elements: the numerator, which is the number of citations in the current year to items published in the previous 2 years, and the denominator, which is the number of substantive articles and reviews published in the same 2 years. The impact factor could just as easily be based on the previous year’s articles alone, which would give even greater weight to rapidly changing fields. An impact factor could also take into account longer periods of citations and sources, but then the measure would be less current.
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TL;DR: Zehn Grundsatze um Forschung zu bewerten, drangen Diana Hicks, Paul Wouters und Kollegen einiges zusammen wirkt.
Abstract: Nutzen Sie diese zehn Grundsatze um Forschung zu bewerten, drangen Diana Hicks, Paul Wouters und Kollegen.
1,437 citations
TL;DR: Tweets can predict highly cited articles within the first 3 days of article publication, and the proposed twimpact factor may be a useful and timely metric to measure uptake of research findings and to filter research findings resonating with the public in real time.
Abstract: Background: Citations in peer-reviewed articles and the impact factor are generally accepted measures of scientific impact Web 20 tools such as Twitter, blogs or social bookmarking tools provide the possibility to construct innovative article-level or journal-level metrics to gauge impact and influence However, the relationship of the these new metrics to traditional metrics such as citations is not known Objective: (1) To explore the feasibility of measuring social impact of and public attention to scholarly articles by analyzing buzz in social media, (2) to explore the dynamics, content, and timing of tweets relative to the publication of a scholarly article, and (3) to explore whether these metrics are sensitive and specific enough to predict highly cited articles Methods: Between July 2008 and November 2011, all tweets containing links to articles in the Journal of Medical Internet Research (JMIR) were mined For a subset of 1573 tweets about 55 articles published between issues 3/2009 and 2/2010, different metrics of social media impact were calculated and compared against subsequent citation data from Scopus and Google Scholar 17 to 29 months later A heuristic to predict the top-cited articles in each issue through tweet metrics was validated Results: A total of 4208 tweets cited 286 distinct JMIR articles The distribution of tweets over the first 30 days after article publication followed a power law (Zipf, Bradford, or Pareto distribution), with most tweets sent on the day when an article was published (1458/3318, 4394% of all tweets in a 60-day period) or on the following day (528/3318, 159%), followed by a rapid decay The Pearson correlations between tweetations and citations were moderate and statistically significant, with correlation coefficients ranging from 42 to 72 for the log-transformed Google Scholar citations, but were less clear for Scopus citations and rank correlations A linear multivariate model with time and tweets as significant predictors (P < 001) could explain 27% of the variation of citations Highly tweeted articles were 11 times more likely to be highly cited than less-tweeted articles (9/12 or 75% of highly tweeted article were highly cited, while only 3/43 or 7% of less-tweeted articles were highly cited; rate ratio 075/007 = 1075, 95% confidence interval, 34–336) Top-cited articles can be predicted from top-tweeted articles with 93% specificity and 75% sensitivity Conclusions: Tweets can predict highly cited articles within the first 3 days of article publication Social media activity either increases citations or reflects the underlying qualities of the article that also predict citations, but the true use of these metrics is to measure the distinct concept of social impact Social impact measures based on tweets are proposed to complement traditional citation metrics The proposed twimpact factor may be a useful and timely metric to measure uptake of research findings and to filter research findings resonating with the public in real time [J Med Internet Res 2011;13(4):e123]
954 citations
Cites background from "The History and Meaning of the Jour..."
...Citations are the basis for metrics like the h-index [1] and its derivatives, which are used to evaluate the productivity and impact of individual researchers, or the impact factor, which is used to evaluate the scientific impact of journals [2]....
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TL;DR: In this article, the authors compared the performance of Web of Science and Scopus and provided a comprehensive comparison of these two databases to answer frequent questions which researchers ask, such as: How web of science and scopus are different? In which aspects these two database are similar? Or, if the researchers are forced to choose one of them, which one should they prefer?
Abstract: Nowadays, the world’s scientific community has been publishing an enormous number of papers in different scientific fields. In such environment, it is essential to know which databases are equally efficient and objective for literature searches. It seems that two most extensive databases are Web of Science and Scopus. Besides searching the literature, these two databases used to rank journals in terms of their productivity and the total citations received to indicate the journals impact, prestige or influence. This article attempts to provide a comprehensive comparison of these databases to answer frequent questions which researchers ask, such as: How Web of Science and Scopus are different? In which aspects these two databases are similar? Or, if the researchers are forced to choose one of them, which one should they prefer? For answering these questions, these two databases will be compared based on their qualitative and quantitative characteristics.
868 citations
TL;DR: Results show that Scopus significantly alters the relative ranking of those scholars that appear in the middle of the rankings and that GS stands out in its coverage of conference proceedings as well as international, non-English language journals.
Abstract: The Institute for Scientific Information's (ISI, now Thomson Scientific, Philadelphia, PA) citation databases have been used for decades as a starting point and often as the only tools for locating citations andsor conducting citation analyses. The ISI databases (or Web of Science [WoS]), however, may no longer be sufficient because new databases and tools that allow citation searching are now available. Using citations to the work of 25 library and information science (LIS) faculty members as a case study, the authors examine the effects of using Scopus and Google Scholar (GS) on the citation counts and rankings of scholars as measured by WoS. Overall, more than 10,000 citing and purportedly citing documents were examined. Results show that Scopus significantly alters the relative ranking of those scholars that appear in the middle of the rankings and that GS stands out in its coverage of conference proceedings as well as international, non-English language journals. The use of Scopus and GS, in addition to WoS, helps reveal a more accurate and comprehensive picture of the scholarly impact of authors. The WoS data took about 100 hours of collecting and processing time, Scopus consumed 200 hours, and GS a grueling 3,000 hours. © 2007 Wiley Periodicals, Inc.
784 citations
TL;DR: In this paper, an in-depth review of the literature on citation impact indicators is provided, focusing on the selection of publications and citations to be included in the calculation of citation impact indicator.
774 citations
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Journal Article•
TL;DR: Procedures are described for measuring protein in solution or after precipitation with acids or other agents, and for the determination of as little as 0.2 gamma of protein.
289,852 citations
TL;DR: This paper describes a method of transferring fragments of DNA from agarose gels to cellulose nitrate filters that can be hybridized to radioactive RNA and hybrids detected by radioautography or fluorography.
30,291 citations
"The History and Meaning of the Jour..." refers background in this paper
...Southern, cited 30 000 times.(12) Since the roughly 60 papers cited more than 10 000 times are decades old, they do not affect the calculation of the current impact factor....
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TL;DR: Overall health risks exceeded benefits from use of combined estrogen plus progestin for an average 5.2-year follow-up among healthy postmenopausal US women, and the results indicate that this regimen should not be initiated or continued for primary prevention of CHD.
Abstract: Context Despite decades of accumulated observational evidence, the balance of risks and benefits for hormone use in healthy postmenopausal women remains uncertain Objective To assess the major health benefits and risks of the most commonly used combined hormone preparation in the United States Design Estrogen plus progestin component of the Women's Health Initiative, a randomized controlled primary prevention trial (planned duration, 85 years) in which 16608 postmenopausal women aged 50-79 years with an intact uterus at baseline were recruited by 40 US clinical centers in 1993-1998 Interventions Participants received conjugated equine estrogens, 0625 mg/d, plus medroxyprogesterone acetate, 25 mg/d, in 1 tablet (n = 8506) or placebo (n = 8102) Main outcomes measures The primary outcome was coronary heart disease (CHD) (nonfatal myocardial infarction and CHD death), with invasive breast cancer as the primary adverse outcome A global index summarizing the balance of risks and benefits included the 2 primary outcomes plus stroke, pulmonary embolism (PE), endometrial cancer, colorectal cancer, hip fracture, and death due to other causes Results On May 31, 2002, after a mean of 52 years of follow-up, the data and safety monitoring board recommended stopping the trial of estrogen plus progestin vs placebo because the test statistic for invasive breast cancer exceeded the stopping boundary for this adverse effect and the global index statistic supported risks exceeding benefits This report includes data on the major clinical outcomes through April 30, 2002 Estimated hazard ratios (HRs) (nominal 95% confidence intervals [CIs]) were as follows: CHD, 129 (102-163) with 286 cases; breast cancer, 126 (100-159) with 290 cases; stroke, 141 (107-185) with 212 cases; PE, 213 (139-325) with 101 cases; colorectal cancer, 063 (043-092) with 112 cases; endometrial cancer, 083 (047-147) with 47 cases; hip fracture, 066 (045-098) with 106 cases; and death due to other causes, 092 (074-114) with 331 cases Corresponding HRs (nominal 95% CIs) for composite outcomes were 122 (109-136) for total cardiovascular disease (arterial and venous disease), 103 (090-117) for total cancer, 076 (069-085) for combined fractures, 098 (082-118) for total mortality, and 115 (103-128) for the global index Absolute excess risks per 10 000 person-years attributable to estrogen plus progestin were 7 more CHD events, 8 more strokes, 8 more PEs, and 8 more invasive breast cancers, while absolute risk reductions per 10 000 person-years were 6 fewer colorectal cancers and 5 fewer hip fractures The absolute excess risk of events included in the global index was 19 per 10 000 person-years Conclusions Overall health risks exceeded benefits from use of combined estrogen plus progestin for an average 52-year follow-up among healthy postmenopausal US women All-cause mortality was not affected during the trial The risk-benefit profile found in this trial is not consistent with the requirements for a viable intervention for primary prevention of chronic diseases, and the results indicate that this regimen should not be initiated or continued for primary prevention of CHD
14,646 citations
TL;DR: The use of conjugated equine estrogen (CEE) increases the risk of stroke, decreases therisk of hip fracture, and does not affect CHD incidence in postmenopausal women with prior hysterectomy over an average of 6.8 years, indicating no overall benefit.
Abstract: Author(s): Anderson, Garnet L; Limacher, Marian; Assaf, Annlouise R; Bassford, Tamsen; Beresford, Shirley AA; Black, Henry; Bonds, Denise; Brunner, Robert; Brzyski, Robert; Caan, Bette; Chlebowski, Rowan; Curb, David; Gass, Margery; Hays, Jennifer; Heiss, Gerardo; Hendrix, Susan; Howard, Barbara V; Hsia, Judith; Hubbell, Allan; Jackson, Rebecca; Johnson, Karen C; Judd, Howard; Kotchen, Jane Morley; Kuller, Lewis; LaCroix, Andrea Z; Lane, Dorothy; Langer, Robert D; Lasser, Norman; Lewis, Cora E; Manson, JoAnn; Margolis, Karen; Ockene, Judith; O'Sullivan, Mary Jo; Phillips, Lawrence; Prentice, Ross L; Ritenbaugh, Cheryl; Robbins, John; Rossouw, Jacques E; Sarto, Gloria; Stefanick, Marcia L; Van Horn, Linda; Wactawski-Wende, Jean; Wallace, Robert; Wassertheil-Smoller, Sylvia; Women's Health Initiative Steering Committee | Abstract: Despite decades of use and considerable research, the role of estrogen alone in preventing chronic diseases in postmenopausal women remains uncertain.To assess the effects on major disease incidence rates of the most commonly used postmenopausal hormone therapy in the United States.A randomized, double-blind, placebo-controlled disease prevention trial (the estrogen-alone component of the Women's Health Initiative [WHI]) conducted in 40 US clinical centers beginning in 1993. Enrolled were 10 739 postmenopausal women, aged 50-79 years, with prior hysterectomy, including 23% of minority race/ethnicity.Women were randomly assigned to receive either 0.625 mg/d of conjugated equine estrogen (CEE) or placebo.The primary outcome was coronary heart disease (CHD) incidence (nonfatal myocardial infarction or CHD death). Invasive breast cancer incidence was the primary safety outcome. A global index of risks and benefits, including these primary outcomes plus stroke, pulmonary embolism (PE), colorectal cancer, hip fracture, and deaths from other causes, was used for summarizing overall effects.In February 2004, after reviewing data through November 30, 2003, the National Institutes of Health (NIH) decided to end the intervention phase of the trial early. Estimated hazard ratios (HRs) (95% confidence intervals [CIs]) for CEE vs placebo for the major clinical outcomes available through February 29, 2004 (average follow-up 6.8 years), were: CHD, 0.91 (0.75-1.12) with 376 cases; breast cancer, 0.77 (0.59-1.01) with 218 cases; stroke, 1.39 (1.10-1.77) with 276 cases; PE, 1.34 (0.87-2.06) with 85 cases; colorectal cancer, 1.08 (0.75-1.55) with 119 cases; and hip fracture, 0.61 (0.41-0.91) with 102 cases. Corresponding results for composite outcomes were: total cardiovascular disease, 1.12 (1.01-1.24); total cancer, 0.93 (0.81-1.07); total fractures, 0.70 (0.63-0.79); total mortality, 1.04 (0.88-1.22), and the global index, 1.01 (0.91-1.12). For the outcomes significantly affected by CEE, there was an absolute excess risk of 12 additional strokes per 10 000 person-years and an absolute risk reduction of 6 fewer hip fractures per 10 000 person-years. The estimated excess risk for all monitored events in the global index was a nonsignificant 2 events per 10 000 person-years.The use of CEE increases the risk of stroke, decreases the risk of hip fracture, and does not affect CHD incidence in postmenopausal women with prior hysterectomy over an average of 6.8 years. A possible reduction in breast cancer risk requires further investigation. The burden of incident disease events was equivalent in the CEE and placebo groups, indicating no overall benefit. Thus, CEE should not be recommended for chronic disease prevention in postmenopausal women.
4,298 citations
TL;DR: In 1971, the Institute for Scientfic Information decided to undertake a systematic analysis of journal citation patterns across the whole of science and technology.
Abstract: As a communications system, the network of journals that play a paramount role in the exchange of scientific and technical information is little understood Periodically since 1927, when Gross and Gross published their study (1) of references in 1 year’s issues of the Journal of the American Chemical Socie/y, pieces of the network have been illuminated by the work of Bradford (2), Allen (3), Gross and Woodford (4), Hooker (5), Henkle (6), Fussier (7), Brown (8), and others (9) Nevertheless, there is still no map of the journal network as a whok To date, studies of the network and of the interrelation of its components have been limited in the number of journak, the areas of scientific study, and the periods of time their authors were able to consider, Such shortcomings have not been due to any lack of purpose, insight, or energy on the part of investigators, but to the practical difficulty of compiling and manipulating manually the enormous amount of necessary data A solution to this problem of data is available in the data base used to produce the Science Citation Index ( SCI ) (10) The coverage of the SCI is international and multidisciplinary; it has grown from 600 journals in 1964 to 2400 journals in 1972, and now includes the world’s most important scientific and technical journals in mow disciplines The SCI is published quarterly and is cumulated annually and quinquennially, but the data base from which the volumes are compiled is maintained on magnetic tape and is updated weekly At the end of 1971, this data base contained more than 27 mi[tion references to about 10 million different published items These references appeared over the past decade in the footnotes and bibliographies of more than 2 million journal articles, communications, letters, and so on The data base is, thus, not only multidisciplinary, it covers a substantial period of time and, being in machine-readable form, is amenable to extensive manipulation by computer In 1971, the Institute for Scientfic Information (1S1) decided to undertake a systematic analysis of journal citation patterns across the whole of science and technology It began by extracting from the data base all references pobIished during the last quarter of 1969 in the 2200 journals then covered by the SCL The resultant sample was about 1 million citations of journals, books, reports, theses, and so forth To test whether this 3-month sample was representative of the year as a whole, it was matched against another sample made by selecting every 27th reference from the approximately 4 million references collected over the entire year The two samples were similar enough in scope (number of diflerent items cited) and detail (relative frequency of their citation by different journals) to
2,560 citations
"The History and Meaning of the Jour..." refers methods in this paper
...Even before the Journal Citation Reports (JCR) appeared, we sampled the 1969 SCI to create the first published ranking by impact factor.(4) Today, the JCR includes every journal citation in more than 5000 journals—about 15 million citations from 1 million source items per year....
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