Tag Archives: Content Marketing

Academic contributions start from concepts and ideas. When their content is relevant and of a high quality they can be published in renowned, peer-reviewed journals. Researchers are increasingly using online full text databases from institutional repositories or online open access journals to disseminate their findings. The web has surely helped to enhance fruitful collaborative relationships among academia. The internet has brought increased engagement among peers, over email or video. In addition, they may share their knowledge with colleagues as they present their papers in seminars and conferences. After publication, their contributions may be cited by other scholars.

The researchers’ visibility does not only rely on the number of publications. Both academic researchers and their institutions are continuously being rated and classified. Their citations may result from highly reputable journals or well-linked homepages providing scientific content. Publications are usually ranked through metrics that will assess individual researchers and their organisational performance. Bibliometrics and citations may be considered as part of the academic reward system. Highly cited authors are usually endorsed by their peers for their significant contribution to knowledge by society. As a matter of fact, citations are at the core of scientometric methods as they have been used to measure the visibility and impact of scholarly work (Moed, 2006; Borgman, 2000). This contribution explores extant literature that explain how the visibility of individual researchers’content may be related to their academic clout. Therefore, it examines the communication structures and processes of scholarly communications (Kousha and Thelwall, 2007; Borgmann and Furner 2002). It presents relevant theoretical underpinnings on bibliometric studies and considers different methods that can analyse the individual researchers’ or their academic publications’ impact (Wilson, 1999; Tague-Sutcliffe, 1992).

 

Citation Analysis
The symbolic role of citation in representing the content of a document is an extensive dimension of information retrieval. Citation analysis expands the scope of information seeking by retrieving publications that have been cited in previous works. This methodology offers enormous possibilities for tracing trends and developments in different research areas. Citation analysis has become the de-facto standard in the evaluation of research. In fact, previous publications can be simply evaluated on the number of citations and the relatively good availability of citation data for such purposes (Knoth and Herrmannova, 2014). However, citations are merely one of the attributes of publications. By themselves, they do not provide adequate and sufficient evidence of impact, quality and research contribution. This may be due to a wide range of characteristics they exhibit; including the semantics of the citation (Knoth and Herrmannova, 2014), the motives for citing (Nicolaisen, 2007), the variations in sentiment (Athar, 2014), the context of the citation (He, Pei, Kifer, Mitra and Giles, 2010), the popularity of topics, the size of research communities (Brumback, 2009; Seglen, 1997), the time delay for citations to show up (Priem and Hemminger, 2010), the skewness of their distribution (Seglen, 1992), the difference in the types of research papers (Seglen, 1997) and finally the ability to game / manipulate citations (Arnold and Fowler, 2010).

Impact Factors (IFs)
Scholarly impact is measure of frequency in which an “average article” has been cited over a defined time period in a journal (Glanzel and Moed, 2002). Journal citations reports are published in June, every year by Thomson-Reuters’ Institute of Scientific Information (ISI). These reports also feature data for ranking the Immediacy Index of articles, which measure the number of times an article appeared in academic citations (Harter, 1996). Publishers of core scientific journals consider IF indicators in their evaluations of prospective contributions. In Despite there are severe limitations in the IF’s methodology, it is still the most common instrument that ranks international journals in any given field of study. Yet, impact factors have often been subject to ongoing criticism by researchers for their methodological and procedural imperfections. Commentators often debate about how IFs should be used. Whilst a higher impact factor may indicate journals that are considered to be more prestigious, it does not necessarily reflect the quality or impact of an individual article or researcher. This may be attributable to the large number of journals, the volume of research contributions, and also the rapidly changing nature of certain research fields and the increasing representation of researchers. Hence, other metrics have been developed to provide alternative measures to impact factors.

h-index
The h-index attempts to calculate the citation impact of the academic publications of researchers. Therefore, this index measures the scholars productivity by taking into account their most cited papers and the number of citations that they received in other publications. This index can also be applied to measure the impact and productivity of a scholarly journal, as well as a group of scientists, such as a department or university or country (Jones, Huggett and Kamalski, 2011). The (Hirsch) h-index was originally developed in 2005 to estimate the importance, significance and the broad impact of an academic’s researcher’s cumulative research contributions. Initially, the h-index was designed to overcome the limitations of other measures of quality and productivity of researchers. It consists of a single number that reports on an author’s academic contributions that have at least the equivalent number of citations. For instance, an h-index of 3 would indicate that the author has published at least three papers that have been cited three times or more. Therefore, the most productive researcher may possibly obtaining a high h-index. Moreover, the best papers in terms of quality will be mostly cited. Interestingly, this issue is driving more researchers to publish in open access journals.

 

Webometrics
The science of webometrics (also cybermetrics) is still in an experimental phase. Björneborn and Ingwersen (2004) indicated that webometrics involves an assessment of different types of hyperlinks. They argued that relevant links may help to improve the impact of academic publications. Therefore, webometrics refer to the quantitative analysis of activity on the world wide web, such as downloads (Davidson, Newton, Ferguson, Daly, Elliott, Homer, Duffield and Jackson, 2014). Webometrics recognise that the internet is a repository for a massive number of documents. It disseminates knowledge to wide audiences. The webometric ranking involves the measurement of volume, visibility, and the impact of web pages. Webometrics emphasise on scientific output including peer-reviewed papers, conference presentations, preprints, monographs, theses, and reports. However, these kind of electronic metrics also analyse other academic material (including courseware, seminar documentation, digital libraries, databases, multimedia, personal pages and blogs among others). Moreover, webometrics consider online information on the educational institution, its departments, research groups, supporting services, and the level of students attending courses.

Web 2.0 and Social Media
Internet users are increasingly creating and publishing their content online. Never before has it been so easy for academics to engage with their peers on both current affairs and scientific findings. The influence of social media has changed the academic publishing scenario. As a matter of fact, recently there has been an increased recognition for measures of scholarly impact to be drawn from Web 2.0 data (Priem and Hemminger, 2010).

The web has not only revolutionised how data is gathered, stored and shared but also provided a mechanism of measuring access to information. Moreover, academics are also using personal web sites and blogs to enhance the visibility of their publications. This medium improves their content marketing in addition to traditional bibliometrics. Social media networks are providing blogging platforms that allows users to communicate to anyone with online access. For instance, Twitter is rapidly becoming used for work related purposes, particularly scholarly communication, as a method of sharing and disseminating information which is central to the work of an academic (Java, Song, Finin and Tseng B, 2007). Recently, there has been rapid growth in the uptake of Twitter by academics to network, share ideas and common interests, and promote their scientific findings (Davidson et al., 2014).

Conclusions and Implications

There are various sources of bibliometric data, each possess their own strengths and limitations. Evidently, there is no single bibliometric measure that is perfect. Multiple approaches to evaluation are highly recommended. Moreover, bibliometric approaches should not be the only measures upon which academic and scholarly performance ought to be evaluated. Sometimes, it may appear that bibliometrics can reduce the publications’ impact to a quantitative, numerical score. Many commentators have argued that when viewed in isolation these metrics may not necessarily be representative of a researcher’s performance or capacity. In taking this view, one would consider bibliometric measures as only one aspect of performance upon which research can be judged. Nonetheless, this chapter indicated that bibliometrics still have their high utility in academia. It is very likely that metrics will to continue to be in use because they represent a relatively simple and accurate data source. For the time being, bibliometrics are an essential aspect of measuring academic clout and organisational performance. A number of systematic ways of assessment have been identified in this regard; including citation analysis, impact factor, h-index and webometrics among others. Notwithstanding, the changes in academic behaviours and their use of content marketing on internet have challenged traditional metrics. Evidently, the measurement of impact beyond citation metrics is an increasing focus among researchers, with social media networks representing the most contemporary way of establishing performance and impact. In conclusion, this contribution suggests that these bibliometrics as well as recognition by peers can help to boost the researchers’, research groups’ and universities’ productivity and their quality of research.

References
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Athar, A. (2014). Sentiment analysis of scientific citations. University of Cambridge, Computer Laboratory, Technical Report, (UCAM-CL-TR-856).

Borgman, C. L. (2000). Digital libraries and the continuum of scholarly communication. Journal of documentation, 56(4), 412-430.

Borgman, C. L., & Furner, J. (2002). Scholarly communication and bibliometrics.

Bornmann, L., & Daniel, H. D. (2005). Does the h-index for ranking of scientists really work?. Scientometrics, 65(3), 391-392.

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Knoth, P., & Herrmannova, D. (2014). Towards Semantometrics: A New Semantic Similarity Based Measure for Assessing a Research Publication’s Contribution. D-Lib Magazine, 20(11), 8.

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