Construction of a blog emotion corpus for Chinese emotional expression analysis

Quan, Changqin; Ren, Fuji

doi:10.3115/1699648.1699691

Cited by 79 publications

(39 citation statements)

References 18 publications

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“…The following criteria guided the data selection process of the EMOBANK corpus: First, complementing existing resources which focus on social media and/or review-style language Quan and Ren, 2009) Second, we conducted a pilot study on two samples (one consisting of movie reviews, the other pulled from a genre-balanced corpus) to compare the IAA resulting from different annotation perspectives (e.g., the writer's and the reader's perspective) in different domains (see Buechel and Hahn (2017) for details). Since we found differences in IAA but the results remained inconclusive, we decided to annotate the whole corpus biperspectivally, i.e., each sentence was rated according to both the (perceived) writer and reader emotion (henceforth, WRITER and READER).…”

Section: Corpus Design and Creationmentioning

confidence: 99%

EmoBank: Studying the Impact of Annotation Perspective and Representation Format on Dimensional Emotion Analysis

Buechel

Hahn

2017

Proceedings of the 15th Conference of the European Chapter of The Association for Computational Linguistics: Volume 2

147

103

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We describe EMOBANK, a corpus of 10k English sentences balancing multiple genres, which we annotated with dimensional emotion metadata in the Valence-ArousalDominance (VAD) representation format. EMOBANK excels with a bi-perspectival and bi-representational design. On the one hand, we distinguish between writer's and reader's emotions, on the other hand, a subset of the corpus complements dimensional VAD annotations with categorical ones based on Basic Emotions. We find evidence for the supremacy of the reader's perspective in terms of IAA and rating intensity, and achieve close-to-human performance when mapping between dimensional and categorical formats.

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Section: Corpus Design and Creationmentioning

confidence: 99%

EmoBank: Studying the Impact of Annotation Perspective and Representation Format on Dimensional Emotion Analysis

Buechel

Hahn

2017

Proceedings of the 15th Conference of the European Chapter of The Association for Computational Linguistics: Volume 2

147

103

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“…The present task involves the identification and tracking of bloggers' emotions with respect to time from Bengali web blog archive 1 . The sections of the bloggers' comments for a given topic contain nested tree like structures along with distinguishable information regarding individual blogger and his/her associated blog posting timestamps.…”

Section: Introductionmentioning

confidence: 99%

“…ENTIMENT Analysis and Opinion Mining have been attempted with more focused perspectives rather than finegrained emotions [1]. In psychology and common use, emotion is an aspect of a person's mental state of being, normally based in or tied to the person's internal (physical) and external (social) sensory feeling [2].…”

Section: Introductionmentioning

confidence: 99%

Tracking Emotions of Bloggers - A Case Study for Bengali

Das¹,

Bandyopadhyay²

2012

Polibits

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Abstract-The present paper describes the identification and tracking of bloggers' emotions with respect to time from the structured Bengali blog documents. The assignment of Ekman's six basic emotions to the bloggers' comments is carried out at sentence and paragraph level granularities. The Referential Informative Chain (RIC) developed for each blogger consists of the nodes representing the emotional states of that blogger. Each node of a RIC contains the identification information of its associated blogger, timestamp, section and emotional sentences. The nodes are arranged in each RIC based on the ascending order of the associated timestamps. An affect scoring technique has been employed to capture the emotions from each of the nodes of a blogger's RIC. The incorporation of self emotions and influential emotions as extracted from other bloggers plays a significant role in detecting the emotions of a blogger's present state. The Extrinsic evaluation produces precision (P), recall (R) and F-Measure of 61.05%, 69.81% and 65.13% respectively for evaluating the total of 193 emotional states of 20 bloggers. The Intrinsic evaluation has been conducted using a manual rater with the help of a statistical agreement coefficient, Krippendorff's alpha α. Two types of alpha, namely nominal alpha and interval alpha produce the average scores of 0.67 and 0.72, respectively.

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“…Those articles are manually annotated with detailed linguistic expressions and emotion tags. [4] as our data source which is manually annotated with both emotion categories and emotion intensities to different level of texts including words, sentences, phrases and documents. Degree words, negative words and conjunctions are also given the corresponding tags respectively as well.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Importance of Modification Relation for Emotional Keywords Annotation and Emotion Types Recognition

Kita²,

Ren³

et al. 2011

IJIES

Self Cite

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Abstract:In this study, we make a scheme to explore the importance of modification relation for the emotional keywords annotation and emotion types recognition. We extract three modification features which are degree words, negative words and conjunctions from the Chinese emotion corpus named Ren-CECps. Beside word and part-ofspeech, three modification relations are adopted as feature in this study. We have carried out eight experiments with different feature sets for emotional keywords annotation and emotion types recognition in sentence level. Eight basic emotion types have been selected and Conditional Random Fields have been employed as the algorithm. In the part of evaluation, we demonstrate the importance of the modification features and our experiment results show the effectiveness of the modification features for improving the performance of emotional keywords annotation and emotion types recognition.

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Construction of a blog emotion corpus for Chinese emotional expression analysis

Cited by 79 publications

References 18 publications

EmoBank: Studying the Impact of Annotation Perspective and Representation Format on Dimensional Emotion Analysis

EmoBank: Studying the Impact of Annotation Perspective and Representation Format on Dimensional Emotion Analysis

Tracking Emotions of Bloggers - A Case Study for Bengali

Exploring the Importance of Modification Relation for Emotional Keywords Annotation and Emotion Types Recognition

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