Do linguistic features of research article titles affect received online attention? A corpus-based analysis
| Date | 29 June 2023 |
| Pages | 2000-2016 |
| DOI | https://doi.org/10.1108/LHT-01-2023-0022 |
| Published date | 29 June 2023 |
| Subject Matter | Library & information science,Librarianship/library management,Library technology,Information behaviour & retrieval,Information user studies,Metadata,Information & knowledge management,Information & communications technology,Internet |
| Author | Haoran Zhu,Xueying Liu |
Do linguistic features of research
article titles affect received online
attention? A corpus-based analysis
Haoran Zhu and Xueying Liu
Huazhong University of Science and Technology, Wuhan, China
Abstract
Purpose –Scientific impact is traditionally assessed with citation-based metrics. Recently, altmetric indices
have been introduced to measure scientific impact both within academia and among the general public.
However, little research has investigated the associationbetween the linguistic features of research article titles
and received online attention. To addressthis issue, the authors examined in the present study the relationship
between a series of title features and altmetric attention scores.
Design/methodology/approach –The data included 8,658 titles of Science articles. The authors extracted
six features from the title corpus (i.e. mean word length, lexical sophistication, lexical density, title length,
syntactic dependency length and sentiment score). The authors performed Spearman’s rank analyses to
analyze the correlations between these features and online impact. The authors then conducted a stepwise
backward multiple regression to identify predictors for the articles’online impact.
Findings –The correlation analyses revealed weak but significant correlations between all six title features
and the altmetric attention scores. The regression analysis showed that four linguistic features of titles (mean
word length, lexical sophistication, title length and sentiment score) have modest predictive effects on the
online impact of research articles.
Originality/value –In the internet era with the widespread use of social media and online platforms, it is
becoming increasingly important for researchers to adapt to the changing context of research evaluation. This
study identifies several linguistic features that deserve scholars’attention in the writing of article titles. It also
has practical implications for academic administrators and pedagogical implications for instructors of
academic writing courses.
Keywords Linguistic features, Altmetrics, Research impact, Titles, Text mining, Online attention
Paper type Case study
1. Introduction
The impact of scientific publications is traditionally assessed with citation-based indices
(Daud et al., 2019), which mainly measure the research impact within the academic community
(Pooladian and Borrego, 2017). However, recent years have witnessed a rapid development of
the internet and increased use of online platforms and social media (e.g. Twitter, Facebook,
Quora and YouTube). Such new platforms provide journal editors and researchers with
opportunities to extend the outreach of scientific publications and have changed the demand,
dissemination and evaluation of scientific knowledge (Yang and Qi, 2021;Wang, 2022). As a
result, academia is becoming increasingly aware of the importance of bridging the gap
between scientific research and the general public by making publications more accessible to
online readers (Alperin et al., 2019;Moradi and Dokhani, 2020).
Against this backdrop, altmetric (short for alternative metric) indices have been designed
to measure the online impact of publications. For example, the Altmetric Attention Score
(AAS) provided by altmetric.com is perhaps the most frequently used alternative bibliometric
indicator (Yang et al., 2021). It is based on a sophisticated algorithm to capture the online
attention a publication has received from various sources, including news websites, blogs,
social network websites and online encyclopedias, among others (Elmore, 2018).
LHT
42,6
2000
Funding: This study was supported by Humanities and Social Sciences Youth Foundation, Ministry of
Education of the People’s Republic of China (Grant No. 21YJC740085).
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0737-8831.htm
Received 24 October 2022
Revised 21 May 2023
Accepted 29 May 2023
Library Hi Tech
Vol. 42 No. 6, 2024
pp. 2000-2016
© Emerald Publishing Limited
0737-8831
DOI 10.1108/LHT-01-2023-0022
Altmetric indices have at least two strengths compared with conventional citation-based
indices (Bornmann, 2014;Pooladian and Borrego, 2016). The first is that altmetric indices
have wider coverage by considering the research impact among non-academic audiences
instead of focusing only on the academic community. The second is that, due to the lag
between the time of publication and citation, traditional metrics are unable to estimate the
research impact immediately after publication. Altmetric indices, by comparison, can reflect
the research impact almost immediately after publication. As such, altmetric indices are often
considered an important complement to traditional bibliometric indicators for research
evaluation (Wang et al., 2020;Lemke et al., 2022).
Recent studies have increasingly focused on identifying factors that may influence the
altmetric indices of research articles. It has been found that altmetric indices are influenced by
both bibliographic factors (such as discipline, publisher, open access status and gender of
authors) and linguistic factors (such as abstract readability). However, the features of article
titles, especially the linguistic aspects of titles, have received much less attention in the
analysis of altmetric indices. Researchers have pointed out that the title is one of the most
important parts of an article (Di Girolamo and Reynders, 2017) since it plays a critical role in
signaling the content of the article and would probably influence the reader’s decision about
whether the article is worth reading or not (Guo et al., 2018;Xiang and Li, 2020). Therefore, a
deeper understanding of the relationship between title features and altmetric indices may
offer insights into certain aspects that deserve the attention of scholars who look to improve
the visibility of their articles, both within and outside academia.
2. Literature review
2.1 Related work on altmetrics
Over the pastdecade, altmetrics has become a hot topicfor research in library and information
sciences (Gonzalez-Valiente et al., 2016;Zhao and Wang, 2020).A number of studies have been
conducted to compare altmetric indices with traditional citation-based ones. For example,
altmetric indices have been found to be correlated with citation-based indices at different
significant levels in many sub-fields of medicine (Batooli et al., 2021;Dixon and Baker, 2022;
Grosh et al., 2022) and in many other disciplines, such as history (Zuccala et al., 2015)and
mathematics (Karmakar et al.,2021). Other studies showed significant correlations between
altmetricindices and the h-index (OliveiraJ E Silva et al., 2021;Nuzzoleseet a l.,2019). In general,
researchers havecome to the agreement that altmetric indicescould be used as a complement
to traditional metrics to achieve more efficient and systemic evaluation of research impact
(Rosenkrantz et al., 2017;Aung et al., 2019;Zhao and Bo, 2020;Wangand Feng, 2022).
Another line of research on altmetrics attempts to uncover the factors that affect altmetric
indices. Discipline has been shown to have an effect on altmetric indices. Htoo and Na (2017),
for example, examined altmetric indices in several social science disciplines and found that
psychiatry, clinical psychology and public health attracted more altmetric mentions than
other disciplines, such as law and political science. Adopting a Principle Component Analysis
(PCA) approach, Ortega (2018) demonstrated that social sciences attracted less attention from
social media platforms than other disciplines. The Open Access (OA) status of research
articles has also been found to have an advantage in attracting online attention (Iglesias-
Puzas et al., 2021). However, such an OA advantage may be restricted to some disciplines and
absent in other disciplines (Holmberg et al., 2020). Moreover, altmetric indices have also been
demonstrated to be influenced by factors such as publisher (Lemke et al., 2022), journal
impact factor (Araujo et al., 2021) and gender of authors (Rotenstein et al., 2022).
In addition to the above-mentioned bibliographic factors, researchers have also paid
attention to the impact of linguistic features on altmetric indices. Some scholars adopted the
methods of discursive analysis and text mining to examine the relationship between abstract
A corpus-based
analysis
2001
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