@inproceedings{zoller2015publication,
  abstract = {Scholarly success is traditionally measured in terms of citations to publications. With the advent of publication man- agement and digital libraries on the web, scholarly usage data has become a target of investigation and new impact metrics computed on such usage data have been proposed – so called altmetrics. In scholarly social bookmarking sys- tems, scientists collect and manage publication meta data and thus reveal their interest in these publications. In this work, we investigate connections between usage metrics and citations, and find posts, exports, and page views of publications to be correlated to citations.},
  author = {Zoller, Daniel and Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd and Hotho, Andreas},
  booktitle = {Proceedings of the 2015 ACM Conference on Web Science},
  interhash = {3515b34cd19959cee5fafbf4467a75ed},
  intrahash = {548a7010ee2726f28e04e5c6e5fd6e2d},
  title = {On Publication Usage in a Social Bookmarking System},
  year = 2015
}

@misc{priem2012altmetrics,
  abstract = {In growing numbers, scholars are integrating social media tools like blogs,
Twitter, and Mendeley into their professional communications. The online,
public nature of these tools exposes and reifies scholarly processes once
hidden and ephemeral. Metrics based on this activities could inform broader,
faster measures of impact, complementing traditional citation metrics. This
study explores the properties of these social media-based metrics or
"altmetrics", sampling 24,331 articles published by the Public Library of
Science.
  We find that that different indicators vary greatly in activity. Around 5% of
sampled articles are cited in Wikipedia, while close to 80% have been included
in at least one Mendeley library. There is, however, an encouraging diversity;
a quarter of articles have nonzero data from five or more different sources.
Correlation and factor analysis suggest citation and altmetrics indicators
track related but distinct impacts, with neither able to describe the complete
picture of scholarly use alone. There are moderate correlations between
Mendeley and Web of Science citation, but many altmetric indicators seem to
measure impact mostly orthogonal to citation. Articles cluster in ways that
suggest five different impact "flavors", capturing impacts of different types
on different audiences; for instance, some articles may be heavily read and
saved by scholars but seldom cited. Together, these findings encourage more
research into altmetrics as complements to traditional citation measures.},
  author = {Priem, Jason and Piwowar, Heather A. and Hemminger, Bradley M.},
  interhash = {629744ad15197eedde33f8444c3e8e01},
  intrahash = {e22613ac29fd25f21430739a4c3e001c},
  note = {cite arxiv:1203.4745v1Comment: 5 tables, 13 figures},
  title = {Altmetrics in the wild: Using social media to explore scholarly impact},
  url = {http://arxiv.org/abs/1203.4745},
  year = 2012
}

@inproceedings{kaur2014scholarometer,
  abstract = {Scholarometer (scholarometer.indiana.edu) is a social tool developed to facilitate citation analysis and help evaluate the impact of authors. The Scholarometer service allows scholars to compute various citation-based impact measures. In exchange, users provide disciplinary annotations of authors, which allow for the computation of discipline-specific statistics and discipline-neutral impact metrics. We present here two improvements of our system. First, we integrated a new universal impact metric hs that uses crowdsourced data to calculate the global rank of a scholar across disciplinary boundaries. Second, improvements made in ambiguous name classification have increased the accuracy from 80% to 87%.},
  acmid = {2615669},
  address = {New York, NY, USA},
  author = {Kaur, Jasleen and JafariAsbagh, Mohsen and Radicchi, Filippo and Menczer, Filippo},
  booktitle = {Proceedings of the 2014 ACM Conference on Web Science},
  doi = {10.1145/2615569.2615669},
  interhash = {bfb4274f2a002cde9efbe71faf295e6a},
  intrahash = {4edc2b8ed7acdd1ef8be4d6eefea8718},
  isbn = {978-1-4503-2622-3},
  location = {Bloomington, Indiana, USA},
  numpages = {2},
  pages = {285--286},
  publisher = {ACM},
  series = {WebSci '14},
  title = {Scholarometer: A System for Crowdsourcing Scholarly Impact Metrics},
  url = {http://doi.acm.org/10.1145/2615569.2615669},
  year = 2014
}

@article{brody2006earlier,
  abstract = {The use of citation counts to assess the impact of research articles is well established. However, the citation impact of an article can only be measured several years after it has been published. As research articles are increasingly accessed through the Web, the number of times an article is downloaded can be instantly recorded and counted. One would expect the number of times an article is read to be related both to the number of times it is cited and to how old the article is. The authors analyze how short-term Web usage impact predicts medium-term citation impact. The physics e-print archive—arXiv.org—is used to test this.},
  author = {Brody, Tim and Harnad, Stevan and Carr, Leslie},
  doi = {10.1002/asi.20373},
  interhash = {b4ae997250ae110bcc89826cb2a8205c},
  intrahash = {643ec09ec9d1fd641c0416c3d8dde8f6},
  issn = {1532-2890},
  journal = {Journal of the American Society for Information Science and Technology},
  number = 8,
  pages = {1060--1072},
  publisher = {Wiley Subscription Services, Inc., A Wiley Company},
  title = {Earlier Web usage statistics as predictors of later citation impact},
  url = {http://dx.doi.org/10.1002/asi.20373},
  volume = 57,
  year = 2006
}

@inproceedings{lipczak2010impact,
  abstract = {Collaborative tagging systems are popular tools for organization, sharing and retrieval of web resources. Their success is due to their freedom and simplicity of use. To post a resource, the user should only define a set of tags that would position the resource in the system's data structure -- folksonomy. This data structure can serve as a rich source of information about relations between tags and concepts they represent. To make use of information collaboratively added to folksonomies, we need to understand how users make tagging decisions. Three factors that are believed to influence user tagging decisions are: the tags used by other users, the organization of user's personal repository and the knowledge model shared between users. In our work we examine the role of another potential factor -- resource title. Despite all the advantages of tags, tagging is a tedious process. To minimize the effort, users are likely to tag with keywords that are easily available. We show that resource title, as a source of useful tags, is easy to access and comprehend. Given a choice of two tags with the same meaning, users are likely to be influenced by their presence in the title. However, a factor that seems to have stronger impact on users' tagging decisions is maintaining the consistency of the personal profile of tags. The results of our study reveal a new, less idealistic picture of collaborative tagging systems, in which the collaborative aspect seems to be less important than personal gains and convenience.},
  acmid = {1810648},
  address = {New York, NY, USA},
  author = {Lipczak, Marek and Milios, Evangelos},
  booktitle = {Proceedings of the 21st ACM Conference on Hypertext and Hypermedia},
  doi = {10.1145/1810617.1810648},
  interhash = {a999b5f2eace0cd75028e57261afe3d7},
  intrahash = {71dd1a473eaf0af9840758653746c221},
  isbn = {978-1-4503-0041-4},
  location = {Toronto, Ontario, Canada},
  numpages = {10},
  pages = {179--188},
  publisher = {ACM},
  series = {HT '10},
  title = {The Impact of Resource Title on Tags in Collaborative Tagging Systems},
  url = {http://doi.acm.org/10.1145/1810617.1810648},
  year = 2010
}

@article{thelwall2012journal,
  abstract = {In theory, the web has the potential to provide information about the wider impact of academic research, beyond traditional scholarly impact. This is because the web can reflect non-scholarly uses of research, such as in online government documents, press coverage or public discussions. Nevertheless, there are practical problems with creating metrics for journals based on web data: principally that most such metrics should be easy for journal editors or publishers to manipulate. Nevertheless, two alternatives seem to have both promise and value: citations derived from digitised books and download counts for journals within specific delivery platforms.},
  author = {Thelwall, Mike},
  doi = {10.1007/s11192-012-0669-x},
  interhash = {834707cf0663109f7811a14ae746be72},
  intrahash = {284883bbaa636a0bab13fc54b903f363},
  issn = {0138-9130},
  journal = {Scientometrics},
  language = {English},
  number = 2,
  pages = {429--441},
  publisher = {Springer Netherlands},
  title = {Journal impact evaluation: a webometric perspective},
  url = {http://dx.doi.org/10.1007/s11192-012-0669-x},
  volume = 92,
  year = 2012
}

@article{thelwall2012journal,
  abstract = {In theory, the web has the potential to provide information about the wider impact of academic research, beyond traditional scholarly impact. This is because the web can reflect non-scholarly uses of research, such as in online government documents, press coverage or public discussions. Nevertheless, there are practical problems with creating metrics for journals based on web data: principally that most such metrics should be easy for journal editors or publishers to manipulate. Nevertheless, two alternatives seem to have both promise and value: citations derived from digitised books and download counts for journals within specific delivery platforms.},
  author = {Thelwall, Mike},
  doi = {10.1007/s11192-012-0669-x},
  interhash = {834707cf0663109f7811a14ae746be72},
  intrahash = {284883bbaa636a0bab13fc54b903f363},
  issn = {0138-9130},
  journal = {Scientometrics},
  language = {English},
  number = 2,
  pages = {429-441},
  publisher = {Springer Netherlands},
  title = {Journal impact evaluation: a webometric perspective},
  url = {http://dx.doi.org/10.1007/s11192-012-0669-x},
  volume = 92,
  year = 2012
}

@article{falagas2008topten,
  abstract = {A considerable part of the scientific community is, at least to some degree, involved in the “impact factor game” Editors strive to increase their journals — impact factor (IF) in order to gain influence in the fields of basic and applied research and scientists seek to profit from the “added value” of publishing in top IF journals. In this article we point out the most common “tricks” of engineering and manipulating the IF undertaken by a portion of professionals of the scientific publishing industry. They attempt to increase the nominator or decrease the denominator of the IF equation by taking advantage of certain design flaws and disadvantages of the IF that permit a degree of artificial and arbitrary inflation. Some of these practices, if not scientifically unethical, are at least questionable and should be abandoned. Editors and publishers should strive for quality through fair and thoughtful selection of papers forwarded for peer review and editorial comments that enhance the quality and scientific accuracy of a manuscript.},
  address = {Basel},
  affiliation = {Alfa Institute of Biomedical Sciences (AIBS) 9 Neapoleos Street 151 23 Marousi, Athens Greece},
  author = {Falagas, Matthew and Alexiou, Vangelis},
  doi = {10.1007/s00005-008-0024-5},
  interhash = {8350623ff88fab4e9405805d9f5663b9},
  intrahash = {4d4a3ba2b742aba8652b347542e39ed9},
  issn = {0004-069X},
  journal = {Archivum Immunologiae et Therapiae Experimentalis},
  keyword = {Biomedical and Life Sciences},
  number = 4,
  pages = {223--226},
  publisher = {Birkhäuser},
  title = {The top-ten in journal impact factor manipulation},
  url = {http://dx.doi.org/10.1007/s00005-008-0024-5},
  volume = 56,
  year = 2008
}

@article{glnzel2002journal,
  abstract = {The Impact Factor introduced by Eugene Garfield is a fundamental citation-based measure for significance and performance of scientific journals. It is perhaps the most popular bibliometric product used in bibliometrics itself, as well as outside the scientific community. First, a concise review of the background and history of the ISI impact factor and the basic ideas underlying it are given. A cross-citation matrix is used to visualise the construction of the Impact Factor and several related journal citation measures},
  author = {Glänzel, Wolfgang and Moed, HenkF.},
  doi = {10.1023/A:1014848323806},
  interhash = {930264a70cc641cb966c63d261133b01},
  intrahash = {b678d6d8afb32c212cf2a4c963ada75e},
  issn = {0138-9130},
  journal = {Scientometrics},
  language = {English},
  number = 2,
  pages = {171-193},
  publisher = {Kluwer Academic Publishers},
  title = {Journal impact measures in bibliometric research},
  url = {http://dx.doi.org/10.1023/A%3A1014848323806},
  volume = 53,
  year = 2002
}

@article{collective2011measuring,
  author = {Collective, Cynical Geographers},
  doi = {10.1111/j.1467-8330.2010.00873.x},
  interhash = {313844c34e760e283a24049a8b5d390c},
  intrahash = {311db90923f95bbc69d64978d06fb0f7},
  issn = {1467-8330},
  journal = {Antipode},
  number = 2,
  pages = {190--194},
  publisher = {Blackwell Publishing Ltd},
  title = {Measuring Impact Beyond Academic Fame: An Alternative Social Impact Factor},
  url = {http://dx.doi.org/10.1111/j.1467-8330.2010.00873.x},
  volume = 43,
  year = 2011
}

@article{collective2011measuring,
  author = {Collective, Cynical Geographers},
  doi = {10.1111/j.1467-8330.2010.00873.x},
  interhash = {313844c34e760e283a24049a8b5d390c},
  intrahash = {311db90923f95bbc69d64978d06fb0f7},
  issn = {1467-8330},
  journal = {Antipode},
  number = 2,
  pages = {190--194},
  publisher = {Blackwell Publishing Ltd},
  title = {Measuring Impact Beyond Academic Fame: An Alternative Social Impact Factor},
  url = {http://dx.doi.org/10.1111/j.1467-8330.2010.00873.x},
  volume = 43,
  year = 2011
}

@article{falagas2008topten,
  abstract = {A considerable part of the scientific community is, at least to some degree, involved in the “impact factor game” Editors strive to increase their journals — impact factor (IF) in order to gain influence in the fields of basic and applied research and scientists seek to profit from the “added value” of publishing in top IF journals. In this article we point out the most common “tricks” of engineering and manipulating the IF undertaken by a portion of professionals of the scientific publishing industry. They attempt to increase the nominator or decrease the denominator of the IF equation by taking advantage of certain design flaws and disadvantages of the IF that permit a degree of artificial and arbitrary inflation. Some of these practices, if not scientifically unethical, are at least questionable and should be abandoned. Editors and publishers should strive for quality through fair and thoughtful selection of papers forwarded for peer review and editorial comments that enhance the quality and scientific accuracy of a manuscript.},
  address = {Basel},
  affiliation = {Alfa Institute of Biomedical Sciences (AIBS) 9 Neapoleos Street 151 23 Marousi, Athens Greece},
  author = {Falagas, Matthew and Alexiou, Vangelis},
  doi = {10.1007/s00005-008-0024-5},
  interhash = {8350623ff88fab4e9405805d9f5663b9},
  intrahash = {46e10496e8530bb408702d2cc58f73e8},
  issn = {0004-069X},
  issue = {4},
  journal = {Archivum Immunologiae et Therapiae Experimentalis},
  keyword = {Biomedical and Life Sciences},
  pages = {223--226},
  publisher = {Birkhäuser},
  title = {The top-ten in journal impact factor manipulation},
  url = {http://dx.doi.org/10.1007/s00005-008-0024-5},
  volume = 56,
  year = 2008
}

@article{thelwall2012journal,
  abstract = {In theory, the web has the potential to provide information about the wider impact of academic research, beyond traditional scholarly impact. This is because the web can reflect non-scholarly uses of research, such as in online government documents, press coverage or public discussions. Nevertheless, there are practical problems with creating metrics for journals based on web data: principally that most such metrics should be easy for journal editors or publishers to manipulate. Nevertheless, two alternatives seem to have both promise and value: citations derived from digitised books and download counts for journals within specific delivery platforms.},
  affiliation = {Statistical Cybermetrics Research Group, School of Technology, University of Wolverhampton, Wulfruna Street, Wolverhampton, WV1 1LY UK},
  author = {Thelwall, Mike},
  doi = {10.1007/s11192-012-0669-x},
  interhash = {834707cf0663109f7811a14ae746be72},
  intrahash = {6b4cb7c71daddfe80cce4f7d75fe11d6},
  issn = {0138-9130},
  journal = {Scientometrics},
  keyword = {Computer Science},
  pages = {1-13},
  publisher = {Akadémiai Kiadó, co-published with Springer Science+Business Media B.V., Formerly Kluwer Academic Publishers B.V.},
  title = {Journal impact evaluation: a webometric perspective},
  url = {http://dx.doi.org/10.1007/s11192-012-0669-x},
  year = {2012 (in press)}
}

@article{priem2010scientometrics,
  abstract = {The growing flood of scholarly literature is exposing the weaknesses of current, citation-based methods of evaluating and filtering articles. A novel and promising approach is to examine the use and citation of articles in a new forum: Web 2.0 services like social bookmarking and microblogging. Metrics based on this data could build a “Scientometics 2.0,” supporting richer and more timely pictures of articles' impact. This paper develops the most comprehensive list of these services to date, assessing the potential value and availability of data from each. We also suggest the next steps toward building and validating metrics drawn from the social Web. },
  author = {Priem, Jason and Hemminger, Bradely H.},
  booktitle = 2010,
  interhash = {d38dfec4da93265575aff99a811839d9},
  intrahash = {6ebe8d305d1fd940e9ae8e89dbe4f0b3},
  journal = {First Monday},
  month = jul,
  number = 7,
  title = {Scientometrics 2.0: New metrics of scholarly impact on the social Web},
  url = {http://www.uic.edu/htbin/cgiwrap/bin/ojs/index.php/fm/article/view/2874/2570},
  volume = 15,
  year = 2010
}

@article{leydesdorff2012alternatives,
  abstract = {Journal Impact Factors (IFs) can be considered historically as the first attempt to normalize citation distributions by using averages over two years. However, it has been recognized that citation distributions vary among fields of science and that one needs to normalize for this. Furthermore, the mean-or any central-tendency statistics-is not a good representation of the citation distribution because these distributions are skewed. Important steps have been taken to solve these two problems during the last few years. First, one can normalize at the article level using the citing audience as the reference set. Second, one can use non-parametric statistics for testing the significance of differences among ratings. A proportion of most-highly cited papers (the top-10% or top-quartile) on the basis of fractional counting of the citations may provide an alternative to the current IF. This indicator is intuitively simple, allows for statistical testing, and accords with the state of the art. },
  author = {Leydesdorff, Loet},
  interhash = {8d14f862a94fb45d31172f8d2a6485fa},
  intrahash = {bd589cc0b6fdfc74b5eea4262c46d3a4},
  journal = {Digital Libraries},
  title = {Alternatives to the Journal Impact Factor: I3 and the Top-10% (or   Top-25%?) of the Most-Highly Cited Papers},
  url = {http://arxiv.org/abs/1201.4638},
  volume = {1201.4638},
  year = 2012
}

@inproceedings{gaugaz2012predicting,
  abstract = {The amount of news content on the Web is increasing: Users can access news articles coming from a variety of sources on the Web: from newswires, news agencies, blogs, and at various places, e.g. even within Web search engines result pages. Anyhow, it still is a challenge for current search engines to decide which news events are worth being shown to the user (either for a newsworthy query or in a news portal). In this paper we define the task of predicting the future impact of news events. Being able to predict event impact will, for example, enable a newspaper to decide whether to follow a specific event or not, or a news search engine which stories to display. We define a flexible framework that, given some definition of impact, can predict its future development at the beginning of the event. We evaluate several possible definitions of event impact and experimentally identify the best features for each of them.},
  author = {Gaugaz, Julien and Siehndel, Patrick and Demartini, Gianluca and Iofciu, Tereza and Georgescu, Mihai and Henze, Nicola},
  booktitle = {Proc. of the 34th European Conference on Information Retrieval (ECIR 2012)},
  interhash = {dc898856b5a18bf1cb9307d1bd9b5268},
  intrahash = {f29c05f9a4fc3bb2189a965d95f622f9},
  location = {Barcelona, Spain},
  month = apr,
  title = {Predicting the Future Impact of News Events},
  url = {http://www.l3s.de/web/page25g.do?kcond12g.att1=1833},
  year = 2012
}

@article{harzing2008becoming,
  abstract = {This editorial asks three questions: What is a high impact journal? How to measure academic impact? What is the academic impact of international business journals? It then discusses EJIM's future as a high impact journal },
  author = {Harzing, Anne-Wil},
  interhash = {a883edd7842eb32718c0e4bb5ba683b8},
  intrahash = {000b37f981ab5a2a5f26b91bad953de5},
  journal = {European Journal of International Management},
  number = 2,
  pages = 115,
  title = {On becoming a high impact journal in international business and management},
  url = {http://inderscience.metapress.com/app/home/contribution.asp?referrer=parent&backto=issue,1,8;journal,15,19;linkingpublicationresults,1:120713,1},
  volume = 2,
  year = 2008
}

@article{bollen2005metrics,
  author = {Bollen, Johan and de Sompel, Herbert Van and Smith, Joan A. and Luce, Rick},
  doi = {DOI: 10.1016/j.ipm.2005.03.024},
  interhash = {e4a18bade26e008fe5488321ec5d6c04},
  intrahash = {01f9e4bea8d03b520dfb618c691e217f},
  issn = {0306-4573},
  journal = {Information Processing & Management},
  note = {Special Issue on Infometrics},
  number = 6,
  pages = {1419 - 1440},
  title = {Toward alternative metrics of journal impact: A comparison of download and citation data},
  url = {http://www.sciencedirect.com/science/article/B6VC8-4GCX1RT-1/2/e68c8a7adfe61acb9d92eb261abd3a43},
  volume = 41,
  year = 2005
}

@inproceedings{bollen2009suggestions,
  abstract = {Most tagging systems support the user in the tag selection process by providing tag suggestions, or recommendations, based on a popularity measurement of tags other users provided when tagging the same resource.  The majority of theories and mathematical models of tagging found in the literature assume that the emergence of power laws in tagging systems is mainly driven by the imitation behavior of users when observing tag suggestions provided by the user interface of the tagging system. We present experimental results that show that the power law distribution forms regardless of whether or not tag suggestions are presented to the users.},
  address = {New York, NY, USA},
  author = {Bollen, Dirk and Halpin, Harry},
  booktitle = {HT '09: Proceedings of the Twentieth ACM Conference on Hypertext and Hypermedia},
  interhash = {280a97ee745f4e0409cf031a1b7ea247},
  intrahash = {d7b14a0eb7fabb3cee8846802de069fe},
  month = {July},
  paperid = {pp161},
  publisher = {ACM},
  session = {Poster},
  title = {The Role of Tag Suggestions in Folksonomies},
  year = 2009
}