Classifying news versus opinions in newspapers: Linguistic features for domain independence

AbstractNewspaper text can be broadly divided in the classes ‘opinion’ (editorials, commentary, letters to the editor) and ‘neutral’ (reports). We describe a classification system for performing this separation, which uses a set of linguistically motivated features. Working with various English newspaper corpora, we demonstrate that it significantly outperforms bag-of-lemma and PoS-tag models. We conclude that the linguistic features constitute the best method for achieving robustness against change of newspaper or domain.

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Towards enhancement of a lexicon-based approach for Saudi dialect sentiment analysis

Journal of Information Science ◽

10.1177/0165551516688143 ◽

2017 ◽

Vol 44 (2) ◽

pp. 184-202 ◽

Cited By ~ 12

Author(s):

Adel Assiri ◽

Ahmed Emam ◽

Hmood Al-Dossari

Keyword(s):

Sentiment Analysis ◽

Large Scale ◽

Training Data ◽

Linguistic Features ◽

Algorithm Development ◽

Domain Independence ◽

Low Performance

Sentiment analysis (SA) techniques are applied to assess aspects of language that are used to express feelings, evaluations and opinions in areas such as customer sentiment extraction. Most studies have focused on SA techniques for widely used languages such as English, but less attention has been paid to Arabic, particularly the Saudi dialect. Most Arabic SA studies have built systems using supervised approaches that are domain dependent; hence, they achieve low performance when applied to a new domain different from the learning domain, and they require manually labelled training data, which are usually difficult to obtain. In this article, we propose a novel lexicon-based algorithm for Saudi dialect SA that features domain independence. We created an annotated Saudi dialect dataset and built a large-scale lexicon for the Saudi dialect. Then, we developed our weighted lexicon-based algorithm. The proposed algorithm mines the associations between polarity and non-polarity words for the dataset and then weights these words based on their associations. During algorithm development, we also proposed novel rules for handling some linguistic features such as negation and supplication. Several experiments were performed to evaluate the performance of the proposed algorithm.

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Linguistic features of the English-language newspaper text of the sports topics

10.18411/lj-05-2020-152 ◽

2020 ◽

Author(s):

A.A. Asylbaeva ◽

N.V. Matveeva

Keyword(s):

English Language ◽

Linguistic Features ◽

Newspaper Text

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Letters to the Editor

Language Speech and Hearing Services in Schools ◽

10.1044/0161-1461.0303.38 ◽

1972 ◽

Vol 3 (3) ◽

pp. 38-39

Author(s):

Jean L. Anderson ◽

Clara B. Weir ◽

Marvin Schnur

Keyword(s):

Letters To The Editor

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Letters to the Editor

Language Speech and Hearing Services in Schools ◽

10.1044/0161-1461.0503.180 ◽

1974 ◽

Vol 5 (3) ◽

pp. 180-181

Author(s):

T. E. Borton ◽

Mary K. White

Keyword(s):

Letters To The Editor

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International Research and Variation in Views of Ethnicity

Perspectives on Global Issues in Communication Sciences and Related Disorders ◽

10.1044/gics2.2.66 ◽

2012 ◽

Vol 2 (2) ◽

pp. 66-72

Author(s):

Ella Inglebret ◽

Amy Skinder-Meredith ◽

Shana Bailey ◽

Carla Jones ◽

Ashley France

Keyword(s):

United States ◽

Classification System ◽

International Research ◽

The United States ◽

Research Articles ◽

Journal Articles ◽

Research Participants ◽

The Past ◽

International Scale ◽

Publication Patterns

The authors in this article first identify the extent to which research articles published in three American Speech-Language-Hearing Association (ASHA) journals included participants, age birth to 18 years, from international backgrounds (i.e., residence outside of the United States), and go on to describe associated publication patterns over the past 12 years. These patterns then provide a context for examining variation in the conceptualization of ethnicity on an international scale. Further, the authors examine terminology and categories used by 11 countries where research participants resided. Each country uses a unique classification system. Thus, it can be expected that descriptions of the ethnic characteristics of international participants involved in research published in ASHA journal articles will widely vary.

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