Although the Scholarometer browser extension is integrated with Google Scholar, Scholarometer is not affiliated with Google Scholar or any Google products. If Google Scholar is missing some papers or citations, that is outside of Scholarometer's control. For any questions about Google Scholar, including how to include your publications, please consult the Google Scholar documentation.
You can create your Google Scholar profile using Google Scholar. Scholarometer is not affiliated with Google Scholar or any Google products. For any questions about Google Scholar please consult the Google Scholar documentation.
Scholarometer is a social (crowdsourcing) tool that leverages the wisdom of the crowds. It requires users to tag authors with one or more field/discipline labels. This generates annotations that go into a database, which collects statistics about the various fields, such as average number of citations per paper, average number of papers per author, etc. This data, in turn, enables the computation of universal citation impact metrics, defined below.
You have to install the Scholarometer extension for your browser (Chrome or Firefox) and then, when you visit an author profile page on Google Scholar, you will see the Scholarometer button at the top right. Click to label the author with fields and see their impact metrics.
Currently we have versions of the extension for Firefox and Google Chrome. At this time we do not expect to develop versions for other browsers, given our limited resources.
We (and others) have asked Google to provide an API to access Google Scholar data. Until such an API becomes available, Scholarometer can only work as a client application, such as a browser extension. Our server is not allowed to query Google Scholar, but you can access the data using your browser.
The hs impact metric is based on field annotations crowdsourced from Scholarometer users. That is why you must apply one or more field tags to annotate the author and their papers. Scholarometer leverages the wisdom of the crowds to collect data about fields.
You may choose from a number of predefined subject categories (marked with an icon), fields provided by other users, or enter your own tags. To aid our collection statistics, at least one predefined discipline is required. The predefined categories are derived from the Web of Science.
An author can be tagged with multiple fields. Each of these annotations is like a vote. We use the number of votes to estimate which fields tags are reliable. If a tag is considered unreliable based on this estimation, it is displayed in grey color.
Scholarometer computes the hs impact metric, proposed by Kaur, Radicchi and Menczer (doi:10.1016/j.joi.2013.09.002 or arxiv:1305.6339). The h-index is defined as the maximum number of articles h such that each has received at least h citations. The hs metric normalizes h by the field average, calculated based on crowdsourced Scholarometer data (the "s" stands for Scholarometer). In this way, the hs index allows to quantitatively compare the impact of authors in different fields, with different citation patterns. Authors with above-average impact have hs > 1, authors with below-average impact have hs < 1. In addition, Scholarometer shows the percentile (%ile) corresponding to a metric, defined as the percentage of authors who have a lower metric value. For example, an author in the 90th %ile has higher impact than 90% of the authors, and lower impact than 10% of the authors. Another way to say this is that the author is in the top 10%. Since hs is computed for each field, an author will have a different percentile for each field, based on the set of authors in that field. Finally, the impact %ile is an annotation-weighted average of hs values across fields. We only consider reliable annotations, based on the number of times an author is tagged with a field.
All impact measures have limitations. While Scholarometer helps authors and academic administrators evaluate the impact of someone's research publications, citation-based impact measures must be carefully interpreted in the context of an author's discipline. Weak impact measures may be explained by factors such as linguistic, geographic, cultural, and disciplinary traditions. If you are going to base important decisions (such as academic tenure or promotion) on impact measures such as those computed by Scholarometer, we recommend that you consult reputable studies on the effectiveness and limitations of such measures in your specific field. Citation-based impact analysis is supposed to be just one of a number of tools in the academic administrator's toolbox. Another caveat in the use of Scholarometer is that the analysis can only be as good as the data source. Google Scholar provides excellent coverage, in many cases better than Web of Science: for example in disciplines such as computer science, which are dominated by conference proceedings; or the social sciences, which are dominated by books. Nevertheless, Google Scholar is based on automatic crawling, parsing, and indexing algorithms, and therefore its data is subject to noise, errors, and possibly incomplete, outdated, and unreliable citation information. For example, it has been shown that by generating fake papers it is possible to trick Google Scholar into boosting an author's citation counts, and therefore to boost the author's impact measures computed by Scholarometer and similar tools. One should not blindly assume that Scholarometer data is reliable and one should always check the underlying data before making any decisions on the basis of citation based impact analysis.
Yes! Check out the Scholarometer API for open, programmatic access to data collected by our platform: field annotations, impact measures, and networks of authors/fields based on shared fields/authors.
The networks are based on crowdsourced field annotations of authors. Two authors are linked if they have similar field profiles. Two fields are linked if they have authors in common. The data for these networks is provided by the Scholarometer API.
The extension/add-on code is available in the Mozilla Firefox Add-ons and Google Chrome Extensions repositories. Additional server-side code is not available at this time.
Unfortunately we do not have time or resources to help individual users. We hope these Frequently Asked Questions will provide sufficient support. Contact us if something is not clear.
If you use Scholarometer, please link to it and share it with your friends and colleagues. If you use Scholarometer in your research, please cite our publications. If you are unsure which papers to cite, we recommend Kaur et al 2012 about the platform and Kaur et al 2013 about the hs index.
Scholarometer is a research project of the Center for Complex Networks and Systems Research (CNetS) at Indiana University. Under the supervision of Fil Menczer, several students have worked on the design and development of the tool: Diep Thi Hoang, Jasleen Kaur, Mohsen JafariAsbagh, Xiaoling Sun, Lino Possamai, Snehal Patil, Wen Chen, and Filipi N. Silva.
Please use the Scholarometer Google Group. You have to join the group in order to post a message.
When you use the Scholarometer extension or visit the Scholarometer Web site, certain information is collected on our Web server, and some information is shared with other sites and services, as described in detail below. Scholarometer does not require registration of user accounts, and does not use cookies. We rely on Google Groups for communication between users and developers, and the use of the Scholarometer Google Group is subject to the terms of use and privacy policy of Google Groups. When you download or update the Scholarometer add-on from the Mozilla Firefox Add-ons site or the Scholarometer extension from the Google Chrome Extensions site, you are subject to the terms of use and privacy policies of the host repositories. We rely on Google Analytics to keep statistics about visitors to the Scholarometer Web site, including use of the server-side scripts that compute impact factors and present results to the users. For debugging purposes, our Web server also logs access information (including client IP addresses) for up to nine weeks. No such personal information will be disclosed to any third parties except if reasonably necessary to satisfy any applicable law and regulation, or to detect and prevent abuse such as spam and vandalism. We automatically post digest information sampled from the latest queries on Twitter, and may make such posts available on the Scholarometer Web site via a Twitter widget. The information posted is subject to the terms of use and privacy policy of Twitter. We may rely on Facebook and Twitter share buttons to allow users to share information about Scholarometer with those third-party services. Usage of those services is subject to the their respective terms of use and privacy policies. We collect query information such as author name(s), keywords, search criteria, and discipline tag annotations. None of the information collected is connected to personal identifying information about the user submitting the query, such as the IP address. The extension passes this bibliographic metadata (tag annotations, query information, and other statistics) to our server. We store this information in the Scholarometer database for the purpose of computing citation based impact measures. Aggregate crowdsourced data is made publicly available via an API. If you do not agree with the privacy policy as detailed above, you should not use the Scholarometer service. This privacy policy was updated in November 2018. Any future changes will be posted here. You may contact us with any questions about this privacy policy as described in the FAQ page.