Automated citation sentiment analysis using high order n-grams: a   preliminary investigation

Muhammad Touseef IKRAM; Muhammad Tanvir AFZAL; Naveed Anwer BUTT

Makale detayları

Automated citation sentiment analysis using high order n-grams: a preliminary investigation

Yazarlar:

Muhammad Touseef IKRAM | Muhammad Tanvir AFZAL | Naveed Anwer BUTT

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2018 Vol.26 Issue 4, pp.1922-1932

Belge Tipi:

Makale

Yayın Tarihi:

7/2018

Belge Dili:

Türkçe

Document ID (Org No.):

2000734945

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

Özet:

 

Scientific papers hold an association with previous   research contributions (i.e. books, journals or conference papers, and web   resources) in the form of citations. Citations are deemed as a link or   relatedness of the previous work to the cited work. The nature of the cited   material could be supportive (positive), contrastive (negative), or   objective (neutral). Extraction of the author's sentiment towards the cited   scientific articles is an emerging research discipline due to various   linguistic differences between the citation sentences and other domains of   sentiment analysis. In this paper, we propose a technique for the   identification of the sentiment of the citing author towards the cited paper   by extracting unigram, bigram, trigram, and pentagram adjective and adverb   patterns from the citation text. After POS tagging of the citation text, we   use the sentence parser for the extraction of linguistic features comprising   adjectives, adverbs, and n-grams from the citation text. A sentiment score   is then assigned to distinguish them as positive, negative, and neutral. In   addition, the proposed technique is compared with manually classified   citation text and 2 commercial tools, namely SEMANTRIA and THEYSAY, to   determine their applicability to the citation corpus. These tools are based   on different techniques for determining the sentiment orientation of the   sentence. Analysis of the results shows that our proposed approach has   achieved results comparable to the commercial counterparts with average   precision, recall, and accuracy of 90{\%}, 81.82{\%}, and 85.91{\%}   respectively.

Makale detayları

Automated citation sentiment analysis using high order n-grams: a preliminary investigation

Yazarlar: Muhammad Touseef IKRAM | Muhammad Tanvir AFZAL | Naveed Anwer BUTT

Yayıncı: TUBITAK

Dergi: Turkish Journal of Electrical Engineering and Computer Science 2018 Vol.26 Issue 4, pp.1922-1932

Belge Tipi: Makale

Yayın Tarihi: 7/2018

Belge Dili: Türkçe

Document ID (Org No.): 2000734945

Sıklık: İki Aylık

eISSN: 1303-6203

pISSN: 1300-0632

Sayı

Yazarlar:

Muhammad Touseef IKRAM | Muhammad Tanvir AFZAL | Naveed Anwer BUTT

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2018 Vol.26 Issue 4, pp.1922-1932

Belge Tipi:

Makale

Yayın Tarihi:

7/2018

Belge Dili:

Türkçe

Document ID (Org No.):

2000734945

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632