This document analyzes the similarity indices of 189 doctoral theses submitted to the University of Calicut after the implementation of a plagiarism check policy in April 2015. The University Library conducted plagiarism checks on the theses using various software. The analysis found that the majority of theses were submitted under the Faculty of Science and by female scholars. It also examined the similarity indices based on factors like faculty, gender, and software used for checking. In general, the similarity levels were found to be within permitted limits set by the university.

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ILIS Journal of Librarianship and Informatics, Vol. 1, No.1 (February 2018)
ILIS Journal of Librarianship and Informatics
Vol. 1, No. 1 (February 2018) pp. 11 – 18
Analysis of Similarity Indices of Doctoral Theses Submitted to the
Calicut University Post-Implementation of
Plagiarism Check Policy
Dr. Vinod V. M.
Assistant Librarian, CHMK Library,
University of Calicut, Kerala
Dr. Abdul Azeez T. A.
Deputy Librarian, CHMK Library,
University of Calicut, Kerala
Abstract
Textual plagiarism is seen to be comon now-a-days in academic writings especially in
theses and dissertations. The University Grants Commission has issued strict norms to ensure
academic honesty in Higher Education Institutions. The University of Calicut, by an administrative
order, has made plagiarism check mandatory for all doctoral theses from April 2015 onwards
and the University Library has been authorized to do the plagiarism check for all theses submitted
to the University using the software issued by INFLIBNET and to furnish the similarity index values
of the component parts – introduction & literature review, methodology and analysis &
interpretation of the theses. Initially ‘Ithenticate’ and ‘Turnitin’ were used for the check and later
changed to ‘Urkund’. The paper is based on the results of plagiarism check of 189 theses subitted
to the University since April 2015. Analysis of the similarity indices of the theses is made with
respect to the Faculty to which they were submitted, gender of the scholars, and software used
for checking.
Keywords : Ithenticate, Plagiarism Policy, Similarity Index, Turnitin, University of Calicut, Urkund
1. Background
Plagiarism, the act of presenting the words,
ideas, work etc of somebody as one’s own, is a
serious academic dishonesty in higher education
institutions and it has always been a problem for
institutions of higher learning. In the contemporary
academic society, with the growth of Internet and
large scale availability of digital resources which can
be readily downloaded, plagiarism has become a
very hot issue for debate and deliberations.
Plagiarism may be intentional or unintentional.
Intentional plagiarism includes purposeful copying,
cut and paste or web publishing without the
permission of creators, whereas, careless
paraphrasing, poor documentation, excessive
quoting or failure to use one’s own voice, comes
under the purview of unintentional plagiarism. Both
cases have to be avoided and while citing other
works, proper acknowledgement has to be given in
the form of citations. There are many reasons for this
unbecoming trend and the major ones are lack of
awareness about plagiarism, lack of command over
English language, explosive growth of Internet,
widespread use of digital resources, poor research
skills, lack of time for reading and understanding,
pressure to publish papers, desire to get immediate
recognition, laziness, fear of failure, google culture
etc.

2. ILIS Journal of Librarianship and Informatics, Vol. 1, No.1 (February 2018)
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1.1 UGC Regulations
The UGC Regulations on Minimum
Standards and Procedures for Award of M.Phil. /
Ph.D. Degree, issued in 2016 has made it
mandatory for every Higher Education Institution
to submit a soft copy of every dissertation or thesis
after successful completion of evaluation and
before announcement of award of the degree, to
the INFLIBNET for hosting the same so as to make
it accessible to all colleges / institutions. Further,
on 1 September 2017, the UGC has released draft
copy of a ‘Regulations 2017’ titled “Promotion of
Academic Integrity and Prevention of Plagiarism
in Higher Education Institutions”. The objectives of
the regulation are :
i. to create academic awareness about
responsible conduct of research, study, project
work, assignment, thesis, dissertation,
promotion of academic integrity and prevention
of misconduct including plagiarism in academic
writing among students, researchers, faculty
and other members of academic staff as well
as any employee of higher education
institutions,
ii. to establish institutional mechanism
through education and training to facilitate
responsible conduct of research, study, project
work, assignment, thesis, dissertation,
promotion of academic integrity and
deterrence from plagiarism and
iii.to develop systems to detect
plagiarism and to set up mechanisms to prevent
plagiarism and punish a student, faculty, or staff
of higher education institution committing the
act of plagiarism.
The UGC regulation mandates some duties
for higher education institutions, such as
conducting of awareness programmes and
trainings; inclusion of the cardinal principles of
academic integrity in the curricula of
Undergraduate / Postgraduate / Master’s degrees
as a compulsory course work; inclusion of elements
of responsible conduct of research and publication
ethics as a compulsory course work for M.Phil. and
Ph.D. Scholars; including elements of responsible
conduct of research and publication ethics in Orientation
and Refresher Courses organized for faculty and other
members of academic staff; training students, faculty,
staff and researchers for using plagiarism detection
tools and reference management tools; establishing
facility equipped with modern technologies for detection
of plagiarism; and encouraging students, faculty, staff
and researchers to register on international researchers’
registry systems. The regulations also contain the
modus operandi of detecting plagiarism in theses and
dissertations and the penalty for different levels of
plagiarism.
1.2 Plagiarism check policy of the
University of Calicut
University of Calicut officially declared its policy
on prevention of plagiarism in an administrative order
in April 2015, and became the first university in Kerala
to make plagiarism check mandatory for all doctoral
theses. The policy document is a comprehensive one
and covers all aspects of plagiarism check including
procedure for plagiarism checking, handling alleged
plagiarism, punishment etc. The University Library has
been authorized to do the plagiarism check on behalf
of the teaching departments and centres of research
affiliated to Calicut University.
As per the Policy on Prevention of Plagiarism, of
the University of Calicut, any of the following acts comes
under the purview of plagiarism.
• Turning in someone else’s work as one’s own;
• Copying words or ideas from someone else, without
giving credit to the original work;
• Failing to put a quotation in quotation marks (?);
• Giving incorrect information about the source of a
quotation;
• Changing words but copying the sentence structure
of a source without giving credit to the original work;
• Copying more than 20 words continuously from a
source, whether you give credit to the original work
or not; and
• Manipulation or misinterpretation of others’ work
(published or unpublished) as her/his own by
modifying numerical values in figures, tables and
illustrations.
Dr. Vinod V. M. & Dr. Abdul Azeez T.A.

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ILIS Journal of Librarianship and Informatics, Vol. 1, No.1 (February 2018)
A thesis, irrespective of the faculty under which it is
to be submitted, consists of three sections viz, Introduction
and Review, Materials and Methods, and Analysis / Result
/ Interpretation / Conclusion etc. The permissible level of
similarity varies between theses submitted under science
/engineering / medicine and non-science subjects. The
difference is only in the case of the section introduction
and review. A similarity index of 35% is permitted in the
case of non-science theses whereas, for science theses
the permissible level is 25% only. For materials and
methods and analysis and result, the permissible level of
similarity are 25% and 10% respectively, irrespective of the
faculty under which it is submitted. Own publications, if
properly acknowledged, are exempted while calculating
the similarity index.
A research scholar has to submit his / her thesis
either in word or pdf format to the University Library in
three parts as mentioned above with a written request for
plagiarism check. There is no need to submit the auxiliary
pages like contents, list of tables and figures, declaration,
certificate, acknowledgment, over leaf pages etc. The files
submitted for plagiarism check are uploaded into the
software and reports in pdf format are either handed over
to the research scholar in person or by email. If the similarity
indexes are within the prescribed limits, a certificate on
plagiarism check is issued in the format prescribed by the
University. In case the similarity index is above the limits,
the research scholar is advised to resubmit the files
concerned with necessary modifications.
The University Library started the mandatory
plagiarism check in the month of April 2015 with the
software supplied by the INFLIBNET. Initially the plagiarism
check was done with ‘Ithenticate’ and ‘Turnitin’ and later
changed to ‘Urkund’. Separate orientation programmes
were conducted for library staff and the academic
community with the assistance of the INFLIBNET to make
them familiar with various aspects of plagiarism.
2. Review of Literature
A survey report on textual plagiarism presented by
Maurer et al (2006) extensively covers the policies of
academic institutions to prevent academic dishonesty; the
three approaches namely, document source comparison,
manual search of characteristic phrases and stylometry;
and the available tools including advanced techniques,
for detecting plagiarism. A few cases of
unexpected effects of plagiarism checking are
also pointed out. Bretag & Mahmud (2009) give
a model for determining student plagiarism by
electronic detection and academic judgement.
A comparison of plagiarism detection
tools is presented by El Tahir Ali et al (2011).
Features of five software / services, namely
PlagAware, PlagScan, and iThenticate, Check
For Plagiarism. net and Plagiarism Detection.
org are covered in the study. Garner (2011)
observes that in biomedical literature (Medline)
alone, about 3,000 new citations that are highly
similar to the ones in previously published
manuscripts appear each year. This
necessitates the editors and reviewers to have
suitable mechanism to identify highly similar
texts in submitted manuscripts so as to maintain
novelty in each paper they publish. The author
further substantiates the relevance of the
software CrossRef and Etblast which are
claimed to be suitable for detecting plagiarism
in biomedical publications. Cross-language
plagiarism detection is the method of
automatically identifying plagiarism in a multi-
lingual context. The paper by Potthast et al (2011)
gives a survey of retrieval models for
assessment of cross language similarity and
compares the three models CL-CNG, CL-ESA
and CL-ASA for the languages English, German,
Spanish, French, Dutch, and Polish.
Ison (2012) reports a study of plagiarism
detected in 100 doctoral dissertations that were
published by institutions granting doctorate
degrees through a primarily online format. The
mean similarity index of these dissertations,
while analysing with Turnitin, was 15.1 with
standard deviation 3.02. The results were then
categorized per previous research. Forty-six
percent of the dissertations were classified as
having a low level of plagiarism while 11% had
a medium level and 3 % had a high level. Further
analysis revealed that 72% of the dissertations
had at least one case of improper paraphrasing
and citation (verbatim text accompanied by a
Analysis of Similarity Indices of Doctoral Theses Submitted
to the Calicut University, Post-Implementation of Plagiarism Check Policy

4. ILIS Journal of Librarianship and Informatics, Vol. 1, No.1 (February 2018)
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citation) and 46% had verbatim text without any
citation. The results emphasize the need for proper
action from the side of faculty, dissertation committee
members, university administrators, and accrediting
bodies, to help reduce the level of plagiarism in
doctoral dissertations. In another study, Ison (2015)
attempted to investigate whether Internet has any
impact on enhancing plagiarism in doctoral
dissertations. A sample 384 dissertations written in
English and published by accredited universities in
the U S and Canada, produced during pre-Internet
and post-Internet eras, was analyzed by Turnitin
software. The mean similarity indices for pre-Internet
and post-Internet eras were 14.5 and 12.3 %,
respectively. A Mann Whitney /U/ test (Mdn =
13, U = 30,098.5, /p/ <0.001) indicated that the
differences between groups was significant. When
comparing the counts of dissertations for each time
era considering those with plagiarism versus those
that had little/no evidence thereof, there was no
statistically significant difference. The final conclusion
is that the Internet has no significant impact on
prevalence of plagiarism in advanced levels of higher
education.
Alzahrani et al (2012) explain how structural
information and citation evidence are used to detect
significant plagiarism cases in scientific publications.
They conducted experiments using a dataset of 15,412
documents divided into 8,657 source publications
and 6,755 suspicious queries, which included 18,147
plagiarism cases inserted automatically. Component-
weight factors are assessed using precision, recall,
and F-measure averaged over a 10-fold cross-
validation and compared using the ANOVA statistical
test. Results from structural-based candidate retrieval
and plagiarism detection are evaluated statistically
against the flat baselines using paired-t tests on 10-
fold cross-validation runs, which demonstrate the
efficacy achieved by the proposed framework. An
empirical study on the system’s response shows that
structural information, unlike the existing plagiarism
detectors, helps to flag significant plagiarism cases,
improve the similarity index, and provide human-like
plagiarism screening results.
Zhang & Jia (2012) attempted a survey to
investigate the use of CrossCheck, powered by
iThenticate, by journal editors to detect plagiarism.
A 22-question survey was sent to 3,305 editors of
scholarly journals in Anglophone countries, and a
reduced 10-question version to 607 editors from non-
Anglophone countries. 42% of all respondents had
used CrossCheck in their work. The major findings
are that plagiarism detection tool and its similarity
report are extremely useful to editors in screening
documents suspected of plagiarism. The editors’
attitude and level of tolerance towards different kinds
of plagiarism vary in different disciplines. Li(2013)
discusses text-based plagiarism, as a serious issue
in scientific publishing. Use of CrossCheck by journals
has sometimes exposed an unexpected amount of
textual similarity between submissions and
databases of scholarly literature. The paper gives an
overview of the relevant literature, to examine how
journal gatekeepers perceive textual appropriation,
and how automated plagiarism-screening tools have
been developed to detect text matching, particularly
for self-check of manuscripts before submission.
Thomas & de Bruin (2015) observes that
plagiarism is common in South African management
journals. High and excessive levels of plagiarism
were detected while analysing 371 published
academic articles that appeared in 19 South African
management journals in 2011 using Turnitin. The cost
to government for subsidising this sort of unoriginal
work in these journals for the period under review
was calculated to be around 7 million ZAR. Debnath
(2016) discusses various types of plagiarism, reasons
for increasingly reported instances of plagiarism, pros
and cons of use of plagiarism detection tools for
detecting plagiarism and role of authors and editors
in preventing/avoiding plagiarism in submitted
manuscripts. Regular usage of professional
plagiarism detection tools for similarity checks with
critical interpretation by the editorial team at the pre-
review stage would help reducing the menace of
plagiarism in submitted manuscripts.
3. The Present Study
The present study aims at identifying the rate
of similarity in the contents of the doctoral theses
submitted in the University of Calicut and share the
experience accumulated with fellow professionals.
4. Methodology
Till date the Calicut University Library has
checked more than two hundred theses and issued
Dr. Vinod V. M. & Dr. Abdul Azeez T.A.

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ILIS Journal of Librarianship and Informatics, Vol. 1, No.1 (February 2018)
Fig. 1 : Faculty-wise Distribution of Theses
5.3 Software used for plagiarism checking
So far the university library has been using
Ithenticate, Turnitin and Urkund for identifying the
content similarity. The number of theses checked
with these software is as shown in fig. 2.
one hundred and eighty nine certificates on
plagiarism check. Data related to the hundred and
eighty nine doctoral theses collected from the internal
records maintained by the University Library are
subjected to analysis. The gender of scholars,
software used for plagiarism check and faculty under
which the thesis is submitted were taken as base for
the analysis. Statistical methods viz. simple arithmetic
mean and percentage were used for data analysis.
5. Analysis
5.1 Gender-wise distribution
Out of the 189 theses submitted for plagiarism
check 82 were of male research scholars and 107 by
female scholars.
5.2 Faculty-wise distribution
The 189 theses checked are from four faculties
– Humanities, Language, Science and Social Science
(fig. 1). The Faculty of Science accounts for 41.27% of
the theses, the share of the Faculty of Social Science
is 31.75%.
5.4. Analysis of similarity index
The result of plagiarism check is often called
similarity index. The literature concerned uses the
term ‘similarity’ deliberately because they firmly
believe that what the software identifies is not
plagiarism but similarity of the document tested, with
other documents already there in the database. The
task of deciding whether the similarity is plagiarism
is left to the experts in the concerned fields. The
similarity index found in the theses of Calicut
University is analysed by using three base variables
viz. faculty, gender and software used for plagiarism
check. The figures given in the tables below are the
respective mean scores.
5.4.1. Faculty-wise similarity index
Similarity indexes of each of the three
constituent parts of the theses, namely Introduction
& review of literature, Methodology, and Analysis &
interpretation, tabulated faculty-wise is given in
Table 1.
With respect to aggregate score, similarity
index is found higher in theses submitted under the
Faculty of Social Sciences and least in the case of
theses under the Faculty of Language. The part-wise
data show that similarity is comparatively higher in
the parts comprising Introduction & Review of
Literature and Methodology. It is obvious that a
researcher may borrow generously from earlier
works to prepare these chapters of the theses.
Naturally the percentage of similarity in these areas
will be on the higher side. On the other hand analysis
and interpretation form the core of the thesis as it is
the original contribution of a research scholar. It is
worthwhile to note that the similarity indexes are least
for analysis part when compared to introduction and
review and methodology. A comparison of the
Fig. 2 : Software Vs the number of theses checked
Analysis of Similarity Indices of Doctoral Theses Submitted
to the Calicut University, Post-Implementation of Plagiarism Check Policy

6. ILIS Journal of Librarianship and Informatics, Vol. 1, No.1 (February 2018)
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their male counterparts, while preparing their theses
except in the case of materials and methods chapter.
5.4.3. Similarity index – Software-wise
The Calicut University Library initially used the
plagiarism detecting software ‘Ithenticate’ and
‘Turnitin’ and then started using ‘Urkund’, which is
continued till date. Both ‘Ithenticate’ and ‘Turnitin’ are
similar in nature; hence the two are grouped under
one head. The approach and philosophy of the
software ‘Urkund’ are entirely different from that of
‘Ithenticate’ and ‘Turnitin’ and hence it is treated
separately. The related data are presented in table3.
similarity indexes with the standards set by the
University clearly shows that the actual results are
well below the set marks. Hence it can be assumed
that the research scholars and their respective guides
do take sufficient care to maintain the originality of
their theses, which in turn keep the similarity index
below the desired level.
5.4.2. Gender-wise analysis of similarity index
Table 2 gives a statement of the similarity
indices categorised according to the gender of the
scholars. Female scholars are slightly better off than
Table 3 : Software-wise statement of Similarity Indices
Sl. No. Section / Part of theses Software-wise Mean Score
Ithenticate / Turnitin Urkund
1 Introduction & Review of Literature 11.442 5.134
2 Methodology (out of 250) 4.500 4.630
3 Analysis (out of 10) 1.242 1.806
4 (Aggregate) 5.728 3.857
Table 1 : Similarity index – Faculty wise
Sl. No. Section / Part of theses
Mean score in the Faculty of —
Humanities Language Science Social Science
1 Introduction & Review of Literature 7.230 4.558 6.076 11.000
2 Methodology (out of 250) 6.705 1.500 6.064 3.800
3 Analysis (out of 10) 1.117 1.000 2.128 1.383
4 (Aggregate) 5.019 2.352 4.756 5.394
Sl. No. Section / Part of theses Gender-wise Mean Score
Male (82) Female (107)
1 Introduction & Review of Literature 8.000 7.065
2 Methodology (out of 250) 4.182 4.887
3 Analysis (out of 10) 1.658 1.551
4 (Aggregate) 4.613 4.500
Table 2 : Similarity index – Gender-wise
Dr. Vinod V. M. & Dr. Abdul Azeez T.A.

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ILIS Journal of Librarianship and Informatics, Vol. 1, No.1 (February 2018)
The aggregate similarity index is found
comparatively low while using ‘Urkund’ for plagiarism
check. But in the case of methodology and analysis
parts, the percentage of similarity is low when
‘Ithenticate’ and ‘Turnitin’ were used. The difference
in the level of similarity may be due to the fact that
while both - ‘Ithenticate’ and ‘Turnitin’ permit
customization, one has to comply with the system
settings for plagiarism check while using ‘Urkund’.
5.4.4. Overall similarity index
This analysis is carried out to know the overall
level of similarity index in the theses submitted in the
Calicut University and its affiliated research centres
without considering the influence of faculty, gender
or software used for plagiarism check. The data is
presented in the following figure.
The data show that the similarity of contents is
more in introduction & review and methodology
areas as expected, and are considerably low
compared to the levels set by the university in its
plagiarism policy. It is a true reflection of the fact that
the research scholars of the university are upholding
the integrity, ethics and academic honesty while
preparing their theses.
6. Findings and Conclusion
The academic community was initially a bit
apprehensive when the plagiarism check was made
mandatory. But their concerns were addressed
through personal guidance and frequent orientation
programmes for both researchers and their guides.
Fig. 3 : Overall similarity index
Since then, the University Library is getting full support
from the research supervisors. It may be noted that
the library is only doing the initial wetting and the
final call is always made by the respective research
council in charge for each departments.
Another point worth mentioning is the fact that
the similarity index shown by the software may not
be a true reflection of the plagiarism. The software
only traces the occurrence of certain number of
words in a sequence in a sentence. Expert human
intervention is required to decide whether the
similarity identified by the software can be termed
plagiarism. Another issue which came across while
doing the plagiarism check is relating to the year of
publication. The software are not year sensitive. If
someone performs the retrospective checking, the
result may contain similarity with sources published
later. Hence going through the date of publication of
both the thesis and source where similarity is found
is strongly recommended.
At present universities in India are following
different yardsticks for identifying plagiarism and
dealing with copyright issues. This may create certain
confusions among the academic community. Hence
the INFLIBNET as an agency spearheading the quality
improvement in the higher education sector in India
may take up a lead role to formulate a uniform
plagiarism policy for the Indian universities. Recently
released UGC draft copy of “Promotion of Academic
Integrity and Prevention of Plagiarism in Higher
Education Institutions Regulations 2017” would be a
first step to achieve the above goal of uniform
plagiarism policy for the Indian universities.
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Introduction
&
Reviews
Methodology
Analysis
Aggregate
Analysis of Similarity Indices of Doctoral Theses Submitted
to the Calicut University, Post-Implementation of Plagiarism Check Policy

8. ILIS Journal of Librarianship and Informatics, Vol. 1, No.1 (February 2018)
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Analysis of Similarity Indices of Doctoral Theses Submitted
to the Calicut University, Post-Implementation of Plagiarism Check Policy
To cite this article :
Vinod, V. M., & Abdul Azeez, T. A. (2018). Analysis of Similarity Indices of Doctoral Theses Submitted to the
Calicut University, Post-Implemenation of Plagiarism Check Policy. ILIS Journal of Librarianship and Informatics,
1(1), 11–18.