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The full text of this paper will be available in October, 2022 due to the embargo policies of Nano Energy. Contact summit@sfu.ca to enquire if the full text of the accepted manuscript can be made available to you.
Author: Nguyen, Thanh, Author: Dinh, Toan, Author: Phan, Hoang-Phuong, Author: Dau, Van Thanh, Author: Perunnilathil Joy, Abbin, Author: Bahreyni, Behraad, Author: and multiple more authors
Date created: 2020-07-02
The full text of this paper will be available in September, 2022 due to the embargo policies of Materials & Design. Contact summit@sfu.ca to enquire if the full text of the accepted manuscript can be made available to you.
Author: Guzman, Pablo, Author: Dinh, Toan, Author: Phan, Hoang-Phuong, Author: Joy, Abbin Perunnilathil, Author: Qamar, Afzaal, Author: Bahreyni, Behraad, Author: Zhu, Yong, Author: Rais-Zadeh, Mina, Author: Li, Huaizhong, Author: Nguyen, Nam-Trung, Author: Dao, Dzung Viet
Date created: 2020-06-27
Author: Perunnilathil Joy, Abbin, Author: Kanygin, Mikhail, Author: Bahreyni, Behraad
Date created: 2019-05-13
The full text of this article will be made available in July 2019 in keeping with the embargo period of the journal Sensors and Actuators A: Physical. If you need access to the full text prior to July 2019, please contact summit@sfu.ca.
Author: Grayli, Siamack V., Author: Leach, Gary W., Author: Bahreyni, Behraad
Date created: 2018-07-09
Author: Shafieia, Mahnaz, Author: El-chamib, Ibrahim, Author: Rintoula, Llew, Author: Bahreyni, Behraad
Date created: 2016-12
The full text of this paper will be available in September, 2021 due to the embargo policies of ACS Applied Polymer Materials. Contact summit@sfu.ca to enquire if the full text of the accepted manuscript can be made available to you.
Author: Kanygin, Mikhail A., Author: Shafiei, Mahnaz, Author: Bahreyni, Behraad
Date created: 2020-09-18
This article is an uncorrected proof of the accepted manuscript.
Author: Shirmohammadli, Vahideh, Author: Bahreyni, Behraad
Date created: 2023-03
The data for this project is a subset of comments from the SFU Opinion and Comments Corpus (SOCC). This subset, the Constructive Comments Corpus (C3) consists of 12, 000 comments annotated by crowdworkers for constructiveness and its characteristics. Citation: Kolhatkar, V., N. Thain, J. Sorensen, L. Dixon and M. Taboada (2020) C3: The Constructive Comments Corpus. Jigsaw and Simon Fraser University. [Data] License: Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
For more information about this work, please see: Kolhatkar, V., N. Thain, J. Sorensen, L. Dixon and M. Taboada (to appear) Classifying Constructive Comments. Journal article under review. http://www.sfu.ca/discourse-lab/.
Other related materials: Kolhatkar, V., H. Wu, L. Cavasso, E. Francis, K. Shukla and M. Taboada The SFU Opinion and Comments Corpus: A corpus for the analysis of online news comments. Corpus Pragmatics. https://doi.org/10.1007/s41701-019-00065-w
To access this data, please contact mtaboada@sfu.ca.
For more information about this work, please see: Kolhatkar, V., N. Thain, J. Sorensen, L. Dixon and M. Taboada (to appear) Classifying Constructive Comments. Journal article under review. http://www.sfu.ca/discourse-lab/.
Other related materials: Kolhatkar, V., H. Wu, L. Cavasso, E. Francis, K. Shukla and M. Taboada The SFU Opinion and Comments Corpus: A corpus for the analysis of online news comments. Corpus Pragmatics. https://doi.org/10.1007/s41701-019-00065-w
To access this data, please contact mtaboada@sfu.ca.
Author: Kolhatkar, Varada, Author: Thain, Nithum, Author: Sorensen, Jeffrey, Author: Dixon, Lucas, Author: Taboada, Maite
Date created: 2020-04-01
The SFU Opinion and Comments Corpus (SOCC) is a corpus for the analysis of online news comments. Our corpus contains comments and the articles from which the comments originated. The articles are all opinion articles, not hard news articles. The corpus is larger than any other currently available comments corpora, and has been collected with attention to preserving reply structures and other metadata. In addition to the raw corpus, we also present annotations for four different phenomena: constructiveness, toxicity, negation and its scope, and appraisal. The data is divided into two main parts: raw data and annotated data. The raw data contains three CSVs: gnm_artcles.csv, gnm_comments.csv, and gnm_comment_threads.csv. The annotated data contains annotations for constructiveness, negation, and appraisal. The details of our different corpora and how to use them are on the following GitHub page. https://github.com/sfu-discourse-lab/SOCC/blob/master/README.md. To access this data, please contact mtaboada@sfu.ca.
Author: Kolhatkar, Varada, Author: Wu, Hanhan, Author: Cavasso, Luca, Author: Francis, Emilie, Author: Shukla, Kavan, Author: Taboada, Maite, Author: Saleem, Mehvish
Date created: 2018-01-18