Internet Research
最新影响因子 - 实时趋势预测 & 排名分区分析


最新

影响因子

2019-2020

4.708

14.6%

影响因子趋势分析

相关期刊

Internet Research

Internet Research 2019-2020 年的影响因子为4.708。

Internet Research Impact Factor
最高影响因子
4.708
最高影响因子 IF

近十年Internet Research的最高影响因子为4.708。

最低影响因子
1.115
最低影响因子 IF

近十年Internet Research的最低影响因子为1.115。

影响因子 总成长率
322.2%
影响因子 总成长率

近十年Internet Research的影响因子总成长率为322.2%。

影响因子 平均成长率
35.8%
影响因子 平均成长率

近十年Internet Research的影响因子平均成长率为35.8%。

影响因子排名分区

子领域 分区 排名 百分比
Economics and Econometrics 1区 25/637

Economics and Econometrics 96%

Communication 1区 6/387

Communication 98%

Sociology and Political Science 1区 14/1243

Sociology and Political Science 98%

影响因子排名分区

· 在Economics and Econometrics研究领域,Internet Research的分区数为1区。Internet Research在Economics and Econometrics研究类别的637种相关期刊中排名第25。在Economics and Econometrics领域,Internet Research的排名百分位约为96%。
· 在Communication研究领域,Internet Research的分区数为1区。Internet Research在Communication研究类别的387种相关期刊中排名第6。在Communication领域,Internet Research的排名百分位约为98%。
· 在Sociology and Political Science研究领域,Internet Research的分区数为1区。Internet Research在Sociology and Political Science研究类别的1243种相关期刊中排名第14。在Sociology and Political Science领域,Internet Research的排名百分位约为98%。

Internet Research Impact Factor 2020-2021 Prediction

Internet Research Impact Factor Predition System

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出版物总数
1277
总引文数
69082

出版数量年度趋势

期刊引用年度趋势

国际合作趋势

引用文献趋势

影响因子历年数据分析

影响因子
影响因子
2019-2020 4.708
2018-2019 4.109
2017-2018 3.838
2016-2017 2.931
2015-2016 3.017
2014-2015 1.661
2013-2014 1.638
2012-2013 1.5
2011-2012 1.115
影响因子历年数据分析

· Internet Research 2019-2020年的影响因子为4.708
· Internet Research 2018-2019年的影响因子为4.109
· Internet Research 2017-2018年的影响因子为3.838
· Internet Research 2016-2017年的影响因子为2.931
· Internet Research 2015-2016年的影响因子为3.017
· Internet Research 2014-2015年的影响因子为1.661
· Internet Research 2013-2014年的影响因子为1.638
· Internet Research 2012-2013年的影响因子为1.5
· Internet Research 2011-2012年的影响因子为1.115

出版物引用数趋势分析

出版数量 引用数量
出版数量 引用数量
1991 9 3
1992 23 38
1993 22 67
1994 26 154
1995 22 221
1996 23 192
1997 36 154
1998 87 227
1999 57 222
2000 49 429
2001 47 633
2002 37 912
2003 39 1176
2004 37 1227
2005 35 1391
2006 32 1863
2007 38 2033
2008 34 2240
2009 33 2927
2010 34 3112
2011 30 3596
2012 33 4180
2013 43 4610
2014 32 5294
2015 41 5326
2016 60 4747
2017 72 4915
2018 49 4012
2019 103 5788
2020 91 6742
2021 3 651
出版物引用数趋势分析

· Internet Research于1991年发表了9篇报告,并取得3篇引用文献。
· Internet Research于1992年发表了23篇报告,并取得38篇引用文献。
· Internet Research于1993年发表了22篇报告,并取得67篇引用文献。
· Internet Research于1994年发表了26篇报告,并取得154篇引用文献。
· Internet Research于1995年发表了22篇报告,并取得221篇引用文献。
· Internet Research于1996年发表了23篇报告,并取得192篇引用文献。
· Internet Research于1997年发表了36篇报告,并取得154篇引用文献。
· Internet Research于1998年发表了87篇报告,并取得227篇引用文献。
· Internet Research于1999年发表了57篇报告,并取得222篇引用文献。
· Internet Research于2000年发表了49篇报告,并取得429篇引用文献。
· Internet Research于2001年发表了47篇报告,并取得633篇引用文献。
· Internet Research于2002年发表了37篇报告,并取得912篇引用文献。
· Internet Research于2003年发表了39篇报告,并取得1176篇引用文献。
· Internet Research于2004年发表了37篇报告,并取得1227篇引用文献。
· Internet Research于2005年发表了35篇报告,并取得1391篇引用文献。
· Internet Research于2006年发表了32篇报告,并取得1863篇引用文献。
· Internet Research于2007年发表了38篇报告,并取得2033篇引用文献。
· Internet Research于2008年发表了34篇报告,并取得2240篇引用文献。
· Internet Research于2009年发表了33篇报告,并取得2927篇引用文献。
· Internet Research于2010年发表了34篇报告,并取得3112篇引用文献。
· Internet Research于2011年发表了30篇报告,并取得3596篇引用文献。
· Internet Research于2012年发表了33篇报告,并取得4180篇引用文献。
· Internet Research于2013年发表了43篇报告,并取得4610篇引用文献。
· Internet Research于2014年发表了32篇报告,并取得5294篇引用文献。
· Internet Research于2015年发表了41篇报告,并取得5326篇引用文献。
· Internet Research于2016年发表了60篇报告,并取得4747篇引用文献。
· Internet Research于2017年发表了72篇报告,并取得4915篇引用文献。
· Internet Research于2018年发表了49篇报告,并取得4012篇引用文献。
· Internet Research于2019年发表了103篇报告,并取得5788篇引用文献。
· Internet Research于2020年发表了91篇报告,并取得6742篇引用文献。
· Internet Research于2021年发表了3篇报告,并取得651篇引用文献。
· Internet Research的总出版物为1277。
· Internet Research的总引用为69082。

Internet Research
基本资讯
Internet Research | Academic Accelerator - About the Journal

介绍

This wide-ranging interdisciplinary journal looks at the social, ethical, economic and political implications of the internet. Recent issues have focused on online and mobile gaming, the sharing economy, and the dark side of social media. None

ISSN
1066-2243
ISSN

Internet Research的ISSN是 1066-2243 ISSN是一个8位数的代码,用于识别各种报纸,期刊,杂志和期刊以及所有媒体 - 包括印刷版和电子版。

ISSN (Online)
-
ISSN (Online)

Internet Research的ISSN(Online)是 - . ISSN是一个8位数的代码,用于识别各种报纸,期刊,杂志和期刊以及所有媒体 - 包括印刷版和电子版。

出版社
Emerald Group Publishing Ltd.
出版社

Internet Research的出版社是 Emerald Group Publishing Ltd.

出版频率
-
出版频率

Internet Research publishes reports - .

出版年度
1991 - Present
出版年度

Internet Research的出版年度包含 1991 - Present .

开放存取
NO
开放存取

Internet Research传统订阅 (non-OA) 期刊。出版商拥有其期刊中文章的版权。任何想要阅读文章的人都应该由个人或机构支付费用来访问这些文章。任何人想以任何方式使用这些文章都必须获得出版商的许可。

出版费
Review
出版费

There is no publication fee for submiting manuscript to Internet Research. Internet Research is Subscription-based (non-OA) Journal. Publishers own the rights to the articles in their journals. Anyone who wants to read the articles should pay by individual or institution to access the articles.

语言
-
语言

The language of Internet Research is - .

国家/地区
United Kingdom
国家/地区

The publisher of Internet Research is Emerald Group Publishing Ltd. , which locates in United Kingdom .

What is Impact Factor?

The impact factor (IF) or journal impact factor (JIF) of an academic journal is a scientometric index calculated by Clarivate that reflects the yearly average number of citations of articles published in the last two years in a given journal. It is frequently used as a proxy for the relative importance of a journal within its field; journals with higher impact factor values are often deemed to be more important, or carry more intrinsic prestige in their respective fields, than those with lower values.

Internet Research | Academic Accelerator - About the Impact Factor

Impact factor is commonly used to evaluate the relative importance of a journal within its field and to measure the frequency with which the “average article” in a journal has been cited in a particular time period. Journal which publishes more review articles will get highest IFs. Journals with higher IFs believed to be more important than those with lower ones. According to Eugene Garfield “impact simply reflects the ability of the journals and editors to attract the best paper available.” Journal which publishes more review articles will get maximum IFs. The Impact Factor of an academic journal is a scientometric Metric that reflects the yearly average number of citations that recent articles published in a given journal received. It is frequently used as a Metric for the relative importance of a journal within its field; journals with higher Impact Factor are often deemed to be more important than those with lower ones. The Internet Research Impact Factor IF measures the average number of citations received in a particular year (2020) by papers published in the Internet Research during the two preceding years (2018-2019). Note that 2020 Impact Factor are reported in 2021; they cannot be calculated until all of the 2020 publications have been processed by the indexing agency. New journals, which are indexed from their first published issue, will receive an impact factor after two years of indexing; in this case, the citations to the year prior to Volume 1, and the number of articles published in the year prior to Volume 1, are known zero values. Journals that are indexed starting with a volume other than the first volume will not get an impact factor until they have been indexed for three years. Occasionally, Journal Citation Reports assigns an impact factor to new journals with less than two years of indexing, based on partial citation data. The calculation always uses two complete and known years of item counts, but for new titles one of the known counts is zero. Annuals and other irregular publications sometimes publish no items in a particular year, affecting the count. The impact factor relates to a specific time period; it is possible to calculate it for any desired period. In addition to the 2-year Impact Factor, the 3-year Impact Factor, 4-year Impact Factor, 5-year Impact Factor, Real-Time Impact Factor can provide further insights and factors into the impact of Internet Research.

History

The impact factor was devised by Eugene Garfield, the founder of the Institute for Scientific Information (ISI). Impact factors are calculated yearly starting from 1975 for journals listed in the Journal Citation Reports (JCR). ISI was acquired by Thomson Scientific & Healthcare in 1992, and became known as Thomson ISI. In 2018, Thomson ISI was sold to Onex Corporation and Baring Private Equity Asia. They founded a new corporation, Clarivate, which is now the publisher of the JCR.

Use

The impact factor is used to compare different journals within a certain field. The Web of Science indexes more than 11,500 science and social science journals. Journal impact factors are often used to evaluate the merit of individual articles and individual researchers. This use of impact factors was summarised by Hoeffel:

Impact Factor is not a perfect tool to measure the quality of articles but there is nothing better and it has the advantage of already being in existence and is, therefore, a good technique for scientific evaluation. Experience has shown that in each specialty the best journals are those in which it is most difficult to have an article accepted, and these are the journals that have a high impact factor. Most of these journals existed long before the impact factor was devised. The use of impact factor as a measure of quality is widespread because it fits well with the opinion we have in each field of the best journals in our specialty....In conclusion, prestigious journals publish papers of high level. Therefore, their impact factor is high, and not the contrary.

Eugene Garfield

In brief, Impact factors may be used by:
  • Authors to decide where to submit an article for publication.
  • Libraries to make collection development decisions
  • Academic departments to assess academic productivity
  • Academic departments to make decisions on promotion and tenure.
As impact factors are a journal-level metric, rather than an article- or individual-level metric, this use is controversial. Garfield agrees with Hoeffel,but warns about the "misuse in evaluating individuals" because there is "a wide variation [of citations] from article to article within a single journal". Other things to consider about Impact Factors:
  • Many journals do not have an impact factor.
  • The impact factor cannot assess the quality of individual articles. Even if citations were evenly distributed among articles, the impact factor would only measure the interests of other researchers in an article, not its importance and usefulness.
  • Only research articles, technical notes and reviews are “citable” items. Editorials, letters, news items and meeting abstracts are “non-citable items”.
  • Only a small percentage of articles are highly cited and they are found in a small subset of journals. This small proportion accounts for a large percentage of citations.
  • Controversial papers, such as those based on fraudulent data, may be highly cited, distorting the impact factor of a journal.
  • Citation bias may exist. For example, English language resources may be favoured. Authors may cite their own work.
Moreover, informed and careful use of these impact data is essential, and should be based on a thorough understanding of the methodology used to generate impact factors. There are controversial aspects of using impact factors:
  • It is not clear whether the number of times a paper is cited measures its actual quality.
  • Some databases that calculate impact factors fail to incorporate publications including textbooks, handbooks and reference books.
  • Certain disciplines have low numbers of journals and usage. Therefore, one should only compare journals or researchers within the same discipline.
  • Review articles normally are cited more often and therefore can skew results.
  • Self-citing may also skew results.
  • Some resources used to calculate impact factors have inadequate international coverage.
  • Editorial policies can artificially inflate an impact factor.
Impact factors have often been used in advancement and tenure decision-making. Many recognize that this is a coarse tool for such important decisions, and that a multitude of factors should be taken into account in these deliberations. When considering the use of the impact factor (IF), keep these aspects in mind:
  • IF analysis is limited to citations from the journals indexed by the Web of Science/Web of Knowledge. Currently, the Web of Science indexes only 8621 journals across the full breadth of the sciences, and just 3121 in the social sciences.
  • A high IF/citation rate says nothing about the quality -- or even, validity -- of the references being cited. Notorious or even retracted articles often attract a lot of attention, hence a high number of citations. The notority related to the first publication on "cold fusion" is one such example.
  • Journals that publish more "review articles" are often found near the top of the rankings. While not known for publishing new, creative findings, these individual articles tend to be heavily cited.
  • The IF measures the average number of citations to articles in the journal -- given this, a small number of highly-cited articles will skew the figure.
  • It takes several years for new journals to be added to the list of titles indexed by the Web of Science/Web of Knowledge, so these newer titles will be under-represented.
  • It's alleged that journal editors have learned to "game" the system, encouraging authors to cite their works previously published in the same journal.
Comparing Journals Across Disciplines? Not a good idea! Using Impact Factors within a given discipline should only be done with great care, as described above. Using impact factor data to compare journals across disciplines is even more problematic. Here are some of the reasons:
  • Disciplines where older literature is still referenced, such as Chemistry and Mathematics, offer challenges to the methodolgy since older citations (older than two years) are not used to calculate the impact factor for a given journal. (Five-year impact factor analysis, which can be calculated using the Journal Citation Index database, helps smooth out this problem only to some degree.)
  • Different disciplines have different practices regarding tendency to cite larger numbers of references. Higher overall citation rates will bump upward impact factor measurements.
  • Where it's common for large numbers of authors to collaborate on a single paper, such as in Physics, the tendency of authors to cite themselves (and in this case, more authors) will result in increased citation rates.

Pros and Cons of the Impact Factor

Pros:

  • A vetted, established metric for measuring journal impact within a discipline.
  • Designed to eliminate bias based on journal size and frequency.
Cons:
  • Individual articles makes an uneven contribution to overall Impact Factor.
  • Impact Factor does not account for certain things, things like context (postive or negative citaion) and intentionality (self-citation).
  • The metric is proprietary to and bound by the contents of the Thomson Reuters database.
  • Citations, on which the Impact Factor is based, count for less than 1% of an article's overall use.

Criticism

Numerous critiques have been made regarding the use of impact factors. A 2007 study noted that the most fundamental flaw is that impact factors present the mean of data that are not normally distributed, and suggested that it would be more appropriate to present the median of these data. There is also a more general debate on the validity of the impact factor as a measure of journal importance and the effect of policies that editors may adopt to boost their impact factor (perhaps to the detriment of readers and writers). Other criticism focuses on the effect of the impact factor on behavior of scholars, editors and other stakeholders. Others have made more general criticisms, arguing that emphasis on impact factor results from negative influence of neoliberal policies on academia claiming that what is needed is not just replacement of the impact factor with more sophisticated metrics for science publications but also discussion on the social value of research assessment and the growing precariousness of scientific careers in higher education.
Experts stress that there are limitations in using impact factors to evaluate a scholar's work. There are many reasons cited for not relying on impact factor alone to evaluate the output of a particular individual. Among these are the following:

  • A single factor is not sufficient for evaluating an author's work.
  • Journal values are meaningless unless compared within the same discipline. Impact factors vary among disciplines.
  • The impact factor was originally devised to show the impact of a specific journal, not a specific scholar. The quality and impact of the author's work may extend beyond the impact of a particular journal.
According to Jim Testa, a researcher for ThomsonReuters Scientific, the most widespread misuse of the Impact Factor is to evaluate the work of an individual author (instead of a journal). "To say that because a researcher is publishing in a certain journal, he or she is more influential or deserves more credit is not necessarily true. There are many other variables to consider." (interview 6/26/2008 in Thomson Reuters blog entry)

什么是影响因子?

影响因子(IF)经常用作表明期刊对其领域重要性的指标。它是由科学信息研究所的创始人Eugene Garfield首次提出的。尽管IF被机构和临床医生广泛使用,但是人们对于IF日记的计算方法,其意义以及如何利用它存在着广泛的误解。期刊的影响因子与同行评议过程的质量和期刊的内容质量等因素无关,而是一种反映对期刊,书籍,论文,项目报告,报纸上发表的文章的平均引用次数的度量,会议/研讨会论文集,在互联网上发布的文件,说明以及任何其他批准的文件。

Internet Research | Academic Accelerator - About the Impact Factor

影响因子通常用于评估期刊在其领域内的相对重要性,以及衡量期刊在特定时间段内引用“平均文章”的频率。发表更多评论文章的期刊将获得最高的IF。 IF较高的期刊被认为比IF较低的期刊更重要。根据尤金·加菲尔德(Eugene Garfield)的说法,“影响只是反映期刊和编辑吸引最佳论文的能力。”发表更多评论文章的期刊将获得最大的IF。