8,321 research outputs found
Utilising content marketing metrics and social networks for academic visibility
There are numerous assumptions on research evaluation in terms of quality and relevance of academic contributions. Researchers are becoming increasingly acquainted with bibliometric indicators, including; citation analysis, impact factor, h-index, webometrics and academic social networking sites. In this light, this chapter presents a review of these concepts as it considers relevant theoretical underpinnings that are related to the content marketing of scholars. Therefore, this contribution critically evaluates previous papers that revolve on the subject of academic reputation as it deliberates on the individual researchers’ personal branding. It also explains how metrics are currently being used to rank the academic standing of journals as well as higher educational institutions. In a nutshell, this chapter implies that the scholarly impact depends on a number of factors including accessibility of publications, peer review of academic work as well as social networking among scholars.peer-reviewe
PageRank: Standing on the shoulders of giants
PageRank is a Web page ranking technique that has been a fundamental
ingredient in the development and success of the Google search engine. The
method is still one of the many signals that Google uses to determine which
pages are most important. The main idea behind PageRank is to determine the
importance of a Web page in terms of the importance assigned to the pages
hyperlinking to it. In fact, this thesis is not new, and has been previously
successfully exploited in different contexts. We review the PageRank method and
link it to some renowned previous techniques that we have found in the fields
of Web information retrieval, bibliometrics, sociometry, and econometrics
Constructing bibliometric networks: A comparison between full and fractional counting
The analysis of bibliometric networks, such as co-authorship, bibliographic
coupling, and co-citation networks, has received a considerable amount of
attention. Much less attention has been paid to the construction of these
networks. We point out that different approaches can be taken to construct a
bibliometric network. Normally the full counting approach is used, but we
propose an alternative fractional counting approach. The basic idea of the
fractional counting approach is that each action, such as co-authoring or
citing a publication, should have equal weight, regardless of for instance the
number of authors, citations, or references of a publication. We present two
empirical analyses in which the full and fractional counting approaches yield
very different results. These analyses deal with co-authorship networks of
universities and bibliographic coupling networks of journals. Based on
theoretical considerations and on the empirical analyses, we conclude that for
many purposes the fractional counting approach is preferable over the full
counting one
Opinion mining and sentiment analysis in marketing communications: a science mapping analysis in Web of Science (1998–2018)
Opinion mining and sentiment analysis has become ubiquitous in our society, with
applications in online searching, computer vision, image understanding, artificial intelligence and
marketing communications (MarCom). Within this context, opinion mining and sentiment analysis
in marketing communications (OMSAMC) has a strong role in the development of the field by
allowing us to understand whether people are satisfied or dissatisfied with our service or product
in order to subsequently analyze the strengths and weaknesses of those consumer experiences. To
the best of our knowledge, there is no science mapping analysis covering the research about opinion
mining and sentiment analysis in the MarCom ecosystem. In this study, we perform a science
mapping analysis on the OMSAMC research, in order to provide an overview of the scientific work
during the last two decades in this interdisciplinary area and to show trends that could be the basis
for future developments in the field. This study was carried out using VOSviewer, CitNetExplorer
and InCites based on results from Web of Science (WoS). The results of this analysis show the
evolution of the field, by highlighting the most notable authors, institutions, keywords,
publications, countries, categories and journals.The research was funded by Programa Operativo FEDER Andalucía 2014‐2020, grant number “La
reputación de las organizaciones en una sociedad digital. Elaboración de una Plataforma Inteligente para la
Localización, Identificación y Clasificación de Influenciadores en los Medios Sociales Digitales (UMA18‐
FEDERJA‐148)” and The APC was funded by the same research gran
Applying weighted PageRank to author citation networks
This paper aims to identify whether different weighted PageRank algorithms
can be applied to author citation networks to measure the popularity and
prestige of a scholar from a citation perspective. Information Retrieval (IR)
was selected as a test field and data from 1956-2008 were collected from Web of
Science (WOS). Weighted PageRank with citation and publication as weighted
vectors were calculated on author citation networks. The results indicate that
both popularity rank and prestige rank were highly correlated with the weighted
PageRank. Principal Component Analysis (PCA) was conducted to detect
relationships among these different measures. For capturing prize winners
within the IR field, prestige rank outperformed all the other measures.Comment: 19 pages, 4 figures, 5 table
- …