The Importance of Fine-Grained Cue Phrases in Scientific Citations (original) (raw)

Toward a Catalogue of Citation-Related Rhetorical Cues in Scientific Texts

Scientific citations establish an explicit network of relationships among mutually relevant articles within a research field. By convention, authors include citations in their papers to indicate works that are foundational in their field, background for their own work, or representative of complementary or contradictory research. But, determining a posteriori the nature of the exact relationship that an author intended between a citing and cited paper is often difficult to ascertain. To address this problem, the aim of formal citation analysis has been to categorize and, ultimately, automatically classify scientific citations. In previous work, Garzone and Mercer (2000) presented a system for citation classification that relied on characteristic syntactic structure to determine citation category. In this present work, we extend this idea to propose a more general catalogue of stylistic and rhetorical techniques that may provide just such an appropriate basis for categorization.

The linguistic patterns and rhetorical structure of citation context: an approach using n-grams

Scientometrics, 2016

Using the full-text corpus of more than 75,000 research articles published by seven PLOS journals, this paper proposes a natural language processing approach for identifying the function of citations. Citation contexts are assigned based on the frequency of n-gram co-occurrences located near the citations. Results show that the most frequent linguistic patterns found in the citation contexts of papers vary according to their location in the IMRaD structure of scientific articles. The presence of negative citations is also dependent on this structure. This methodology offers new perspectives to locate these discursive forms according to the rhetorical structure of scientific articles, and will lead to a better understanding of the use of citations in scientific articles.

Automatic classification of citation function

Proceedings of the 2006 …, 2006

Citation function is defined as the author's reason for citing a given paper (e.g. acknowledgement of the use of the cited method). The automatic recognition of the rhetorical function of citations in scientific text has many applications, from improvement of impact factor calculations to text summarisation and more informative citation indexers. We show that our annotation scheme for citation function is reliable, and present a supervised machine learning framework to automatically classify citation function, using both shallow and linguistically-inspired features. We find, amongst other things, a strong relationship between citation function and sentiment classification.

Towards the Automatic Identification of the Nature of Citations

The reasons why an author cites other publications are varied: an author can cite previous works to gain assistance of some sort in the form of background information, ideas, methods, or to review, critique or refute previous works. The problem is that the best possible way to retrieve the nature of citations is very time consuming: one should read article by article to assign a particular characterisation to each citation. In this paper we propose an algorithm, called CiTalO, to infer automatically the function of citations by means of Semantic Web technologies and NLP techniques. We also present some preliminary experiments and discuss some strengths and limitations of this approach.

Using Hedges to Classify Citations in Scientific Articles

2000

Citations in scientific writing fulfil an important role in creating relationships among mutually relevant articles within a research field. These inter-article relationships reinforce the argumentation structure intrinsic to all scientific writing. Therefore, determining the nature of the exact relationship between a citing and cited paper requires an understanding of the rhetorical relations within the argumentative context in which a citation

Semantic Classification of the Citations

—In this study the semantic classification of the references/citations of a scientific article according to position within the article is investigated. For this purpose, the article is divided into two major sections: the Introduction/Background section and the rest section which contains the methodology, experimental part, results and conclusion parts. Additionally, the references of an article are divided into two categories: the Self-References and the Citations which are used for the semantic interpretation of the references in combination with the aforementioned geographic partition. For achievement of this, an algorithm was constructed which was implemented using Java programming language and was applied in a numerous articles of open springer journals. Finally, the classification results as well as the interpretation of these should create a new consideration about the contribution of each reference in the knowledge creation specifically in the self-citation case.

What Sentence are you Referring to and Why? Identifying Cited Sentences in Scientific Literature

2017

In the current context of scientific information overload, text mining tools are of paramount importance for researchers who have to read scientific papers and assess their value. Current citation networks, which link papers by citation relationships (reference and citing paper), are useful to quantitatively understand the value of a piece of scientific work, however they are limited in that they do not provide information about what specific part of the reference paper the citing paper is referring to. This qualitative information is very important, for example, in the context of current community-based scientific summarization activities. In this paper, and relying on an annotated dataset of co-citation sentences, we carry out a number of experiments aimed at, given a citation sentence, automatically identify a part of a reference paper being cited. Additionally our algorithm predicts the specific reason why such reference sentence has been cited out of five possible reasons.

Mapping the linguistic context of citations

Bulletin of the Association for Information Science and Technology, 2015

EDITOR'S SUMMARYScientific papers are routinely structured in sections for introduction, methods, research and discussion, a standard since the 1970s. Citations originating within each section serve different purposes and can be meaningfully classified according to position, shedding light on an author's purpose for the citation. Furthermore, words near the citations in the various sections differ, providing the basis for lexical and semantic analysis of citation contexts. Approximately 50,000 scientific papers from seven PLOS journals published between 2009 and 2012 were analyzed for citation use within the identifiable document structure and for verbs used in the context of the citations. Frequencies of verbs in the four section types demonstrate the predominant use of certain words by section. Introduction sections showed greater variety of verbs, while a more limited range of verbs was seen in Methods sections. The lexical distribution process may be applied to other con...

An annotation scheme for citation function

… of the 7th SIGdial Workshop on …, 2009

We study the interplay of the discourse structure of a scientific argument with formal citations. One subproblem of this is to classify academic citations in scientific articles according to their rhetorical function, e.g., as a rival approach, as a part of the solution, or as a flawed approach that justifies the current research. Here, we introduce our annotation scheme with 12 categories, and present an agreement study.