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SentiSynset

This repository is for the paper Identifying Emotional and Polar Concepts via Synset Translation. In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), pages 142–152, Mexico City, Mexico. Association for Computational Linguistics.

[Paper] [Poster] [Slides]

Directory

  • emolex - English and translated multingual NRC Emotion Lexicons (EmoLex)
  • generated_files - Intermediary files generated while creating SentiSynset
SentiSynset
├─── assets
| ├─── paper.pdf
| ├─── poster.pdf
| └─── slides.pdf
├─── emolex
| ├─── NRC-Emotion-Lexicon-Wordlevel-v0.92.txt
| └─── OneFilePerLanguage
| ├─── Afrikaans-NRC-EmoLex.txt
| ├─── Albanian-NRC-EmoLex.txt
| ├─── ...
| └─── Zulu-NRC-EmoLex.txt
├─── generated_files
| ├─── all_wn_translations.pkl
| ├─── lemmatized_multilingual_lexicons.pkl
| ├─── non_sentiment_normalized_lemmatized_multilingual_lexicons.pkl
| └─── normalized_lemmatized_multilingual_lexicons.pkl
├───.gitignore
├─── babelnet_conf.yml
├─── create_lexicons.py
├─── load_multingual_translations.py
├─── main.py
├─── README.md
├─── requirements.txt
├─── select_languages.pkl
├─── sentisynset_lexicon.xml
└─── translations.py

Dependencies

  • python == 3.8
  • babelnet == 1.1.0
  • langcodes == 3.4.0
  • nltk == 3.8.1
  • simplemma == 0.9.1
  • spacy == 3.7.5
  • Unidecode == 1.3.8
  • xmltodict == 0.13.0

Setup

Please ensure required packages are already installed. A virtual environment is recommended.

$ cd SentiSynset
$ pip install pip --upgrade
$ pip install -r requirements.txt

Run

The script needs to be able to read data from a local copy of the BabelNet indices (you cannot use the BabelNet API in online mode as you will quickly exceed the daily requests limit). Note that the BabelNet API requires Python 3.8.

$ python3 main.py

Authors

BibTex

@inproceedings{woudstra-etal-2024-identifying,
title = "Identifying Emotional and Polar Concepts via Synset Translation",
author = "Woudstra, Logan and Dawodu, Moyo and Igwe, Frances and Li, Senyu and Shi, Ning and Hauer, Bradley and Kondrak, Grzegorz",
editor = "Bollegala, Danushka and Shwartz, Vered",
booktitle = "Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024)",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.starsem-1.12",
pages = "142--152",
abstract = "Emotion identification and polarity classification seek to determine the sentiment expressed by a writer. Sentiment lexicons that provide classifications at the word level fail to distinguish between different senses of polysemous words. To address this problem, we propose a translation-based method for labeling each individual lexical concept and word sense. Specifically, we translate synsets into 20 different languages and verify the sentiment of these translations in multilingual sentiment lexicons. By applying our method to all WordNet synsets, we produce SentiSynset, a synset-level sentiment resource containing 12,429 emotional synsets and 15,567 polar synsets, which is significantly larger than previous resources. Experimental evaluation shows that our method outperforms prior automated methods that classify word senses, in addition to outperforming ChatGPT. We make the resulting resource publicly available on GitHub.",
}

About

This repository is for the paper Identifying Emotional and Polar Concepts via Synset Translation. In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), Mexico City, Mexico. Association for Computational Linguistics.

aclanthology.org/2024.starsem-1.12/

Topics

emotionnaaclnaacl-papernaacl2024polaritystar-semsynsettranslation

Resources

Readme
Activity
Custom properties

Stars

0 stars

Watchers

2 watching

Forks

0 forks
Report repository

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Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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var __m = "github.com";
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SentiSynset
This repository is for the paper Identifying Emotional and Polar Concepts via Synset Translation. In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), pages 142–152, Mexico City, Mexico. Association for Computational Linguistics.
[Paper] [Poster] [Slides]
Directory
  • emolex - English and translated multingual NRC Emotion Lexicons (EmoLex)
  • generated_files - Intermediary files generated while creating SentiSynset
SentiSynset
├─── assets
| ├─── paper.pdf
| ├─── poster.pdf
| └─── slides.pdf
├─── emolex
| ├─── NRC-Emotion-Lexicon-Wordlevel-v0.92.txt
| └─── OneFilePerLanguage
| ├─── Afrikaans-NRC-EmoLex.txt
| ├─── Albanian-NRC-EmoLex.txt
| ├─── ...
| └─── Zulu-NRC-EmoLex.txt
├─── generated_files
| ├─── all_wn_translations.pkl
| ├─── lemmatized_multilingual_lexicons.pkl
| ├─── non_sentiment_normalized_lemmatized_multilingual_lexicons.pkl
| └─── normalized_lemmatized_multilingual_lexicons.pkl
├───.gitignore
├─── babelnet_conf.yml
├─── create_lexicons.py
├─── load_multingual_translations.py
├─── main.py
├─── README.md
├─── requirements.txt
├─── select_languages.pkl
├─── sentisynset_lexicon.xml
└─── translations.py

Dependencies
  • python == 3.8
  • babelnet == 1.1.0
  • langcodes == 3.4.0
  • nltk == 3.8.1
  • simplemma == 0.9.1
  • spacy == 3.7.5
  • Unidecode == 1.3.8
  • xmltodict == 0.13.0
Setup
Please ensure required packages are already installed. A virtual environment is recommended.
$ cd SentiSynset
$ pip install pip --upgrade
$ pip install -r requirements.txt
Run
The script needs to be able to read data from a local copy of the BabelNet indices (you cannot use the BabelNet API in online mode as you will quickly exceed the daily requests limit). Note that the BabelNet API requires Python 3.8.
$ python3 main.py
Authors
BibTex
@inproceedings{woudstra-etal-2024-identifying,
title = "Identifying Emotional and Polar Concepts via Synset Translation",
author = "Woudstra, Logan and Dawodu, Moyo and Igwe, Frances and Li, Senyu and Shi, Ning and Hauer, Bradley and Kondrak, Grzegorz",
editor = "Bollegala, Danushka and Shwartz, Vered",
booktitle = "Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024)",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.starsem-1.12",
pages = "142--152",
abstract = "Emotion identification and polarity classification seek to determine the sentiment expressed by a writer. Sentiment lexicons that provide classifications at the word level fail to distinguish between different senses of polysemous words. To address this problem, we propose a translation-based method for labeling each individual lexical concept and word sense. Specifically, we translate synsets into 20 different languages and verify the sentiment of these translations in multilingual sentiment lexicons. By applying our method to all WordNet synsets, we produce SentiSynset, a synset-level sentiment resource containing 12,429 emotional synsets and 15,567 polar synsets, which is significantly larger than previous resources. Experimental evaluation shows that our method outperforms prior automated methods that classify word senses, in addition to outperforming ChatGPT. We make the resulting resource publicly available on GitHub.",
}
About
This repository is for the paper Identifying Emotional and Polar Concepts via Synset Translation. In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), Mexico City, Mexico. Association for Computational Linguistics.
aclanthology.org/2024.starsem-1.12/
Topics
emotionnaaclnaacl-papernaacl2024polaritystar-semsynsettranslation
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
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} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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SentiSynset
This repository is for the paper Identifying Emotional and Polar Concepts via Synset Translation. In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), pages 142–152, Mexico City, Mexico. Association for Computational Linguistics.
[Paper] [Poster] [Slides]
Directory
  • emolex - English and translated multingual NRC Emotion Lexicons (EmoLex)
  • generated_files - Intermediary files generated while creating SentiSynset
SentiSynset
├─── assets
| ├─── paper.pdf
| ├─── poster.pdf
| └─── slides.pdf
├─── emolex
| ├─── NRC-Emotion-Lexicon-Wordlevel-v0.92.txt
| └─── OneFilePerLanguage
| ├─── Afrikaans-NRC-EmoLex.txt
| ├─── Albanian-NRC-EmoLex.txt
| ├─── ...
| └─── Zulu-NRC-EmoLex.txt
├─── generated_files
| ├─── all_wn_translations.pkl
| ├─── lemmatized_multilingual_lexicons.pkl
| ├─── non_sentiment_normalized_lemmatized_multilingual_lexicons.pkl
| └─── normalized_lemmatized_multilingual_lexicons.pkl
├───.gitignore
├─── babelnet_conf.yml
├─── create_lexicons.py
├─── load_multingual_translations.py
├─── main.py
├─── README.md
├─── requirements.txt
├─── select_languages.pkl
├─── sentisynset_lexicon.xml
└─── translations.py

Dependencies
  • python == 3.8
  • babelnet == 1.1.0
  • langcodes == 3.4.0
  • nltk == 3.8.1
  • simplemma == 0.9.1
  • spacy == 3.7.5
  • Unidecode == 1.3.8
  • xmltodict == 0.13.0
Setup
Please ensure required packages are already installed. A virtual environment is recommended.
$ cd SentiSynset
$ pip install pip --upgrade
$ pip install -r requirements.txt
Run
The script needs to be able to read data from a local copy of the BabelNet indices (you cannot use the BabelNet API in online mode as you will quickly exceed the daily requests limit). Note that the BabelNet API requires Python 3.8.
$ python3 main.py
Authors
BibTex
@inproceedings{woudstra-etal-2024-identifying,
title = "Identifying Emotional and Polar Concepts via Synset Translation",
author = "Woudstra, Logan and Dawodu, Moyo and Igwe, Frances and Li, Senyu and Shi, Ning and Hauer, Bradley and Kondrak, Grzegorz",
editor = "Bollegala, Danushka and Shwartz, Vered",
booktitle = "Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024)",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.starsem-1.12",
pages = "142--152",
abstract = "Emotion identification and polarity classification seek to determine the sentiment expressed by a writer. Sentiment lexicons that provide classifications at the word level fail to distinguish between different senses of polysemous words. To address this problem, we propose a translation-based method for labeling each individual lexical concept and word sense. Specifically, we translate synsets into 20 different languages and verify the sentiment of these translations in multilingual sentiment lexicons. By applying our method to all WordNet synsets, we produce SentiSynset, a synset-level sentiment resource containing 12,429 emotional synsets and 15,567 polar synsets, which is significantly larger than previous resources. Experimental evaluation shows that our method outperforms prior automated methods that classify word senses, in addition to outperforming ChatGPT. We make the resulting resource publicly available on GitHub.",
}
About
This repository is for the paper Identifying Emotional and Polar Concepts via Synset Translation. In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), Mexico City, Mexico. Association for Computational Linguistics.
aclanthology.org/2024.starsem-1.12/
Topics
emotionnaaclnaacl-papernaacl2024polaritystar-semsynsettranslation
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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SentiSynset
This repository is for the paper Identifying Emotional and Polar Concepts via Synset Translation. In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), pages 142–152, Mexico City, Mexico. Association for Computational Linguistics.
[Paper] [Poster] [Slides]
Directory
  • emolex - English and translated multingual NRC Emotion Lexicons (EmoLex)
  • generated_files - Intermediary files generated while creating SentiSynset
SentiSynset
├─── assets
| ├─── paper.pdf
| ├─── poster.pdf
| └─── slides.pdf
├─── emolex
| ├─── NRC-Emotion-Lexicon-Wordlevel-v0.92.txt
| └─── OneFilePerLanguage
| ├─── Afrikaans-NRC-EmoLex.txt
| ├─── Albanian-NRC-EmoLex.txt
| ├─── ...
| └─── Zulu-NRC-EmoLex.txt
├─── generated_files
| ├─── all_wn_translations.pkl
| ├─── lemmatized_multilingual_lexicons.pkl
| ├─── non_sentiment_normalized_lemmatized_multilingual_lexicons.pkl
| └─── normalized_lemmatized_multilingual_lexicons.pkl
├───.gitignore
├─── babelnet_conf.yml
├─── create_lexicons.py
├─── load_multingual_translations.py
├─── main.py
├─── README.md
├─── requirements.txt
├─── select_languages.pkl
├─── sentisynset_lexicon.xml
└─── translations.py

Dependencies
  • python == 3.8
  • babelnet == 1.1.0
  • langcodes == 3.4.0
  • nltk == 3.8.1
  • simplemma == 0.9.1
  • spacy == 3.7.5
  • Unidecode == 1.3.8
  • xmltodict == 0.13.0
Setup
Please ensure required packages are already installed. A virtual environment is recommended.
$ cd SentiSynset
$ pip install pip --upgrade
$ pip install -r requirements.txt
Run
The script needs to be able to read data from a local copy of the BabelNet indices (you cannot use the BabelNet API in online mode as you will quickly exceed the daily requests limit). Note that the BabelNet API requires Python 3.8.
$ python3 main.py
Authors
BibTex
@inproceedings{woudstra-etal-2024-identifying,
title = "Identifying Emotional and Polar Concepts via Synset Translation",
author = "Woudstra, Logan and Dawodu, Moyo and Igwe, Frances and Li, Senyu and Shi, Ning and Hauer, Bradley and Kondrak, Grzegorz",
editor = "Bollegala, Danushka and Shwartz, Vered",
booktitle = "Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024)",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.starsem-1.12",
pages = "142--152",
abstract = "Emotion identification and polarity classification seek to determine the sentiment expressed by a writer. Sentiment lexicons that provide classifications at the word level fail to distinguish between different senses of polysemous words. To address this problem, we propose a translation-based method for labeling each individual lexical concept and word sense. Specifically, we translate synsets into 20 different languages and verify the sentiment of these translations in multilingual sentiment lexicons. By applying our method to all WordNet synsets, we produce SentiSynset, a synset-level sentiment resource containing 12,429 emotional synsets and 15,567 polar synsets, which is significantly larger than previous resources. Experimental evaluation shows that our method outperforms prior automated methods that classify word senses, in addition to outperforming ChatGPT. We make the resulting resource publicly available on GitHub.",
}
About
This repository is for the paper Identifying Emotional and Polar Concepts via Synset Translation. In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), Mexico City, Mexico. Association for Computational Linguistics.
aclanthology.org/2024.starsem-1.12/
Topics
emotionnaaclnaacl-papernaacl2024polaritystar-semsynsettranslation
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
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})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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SentiSynset
This repository is for the paper Identifying Emotional and Polar Concepts via Synset Translation. In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), pages 142–152, Mexico City, Mexico. Association for Computational Linguistics.
[Paper] [Poster] [Slides]
Directory
  • emolex - English and translated multingual NRC Emotion Lexicons (EmoLex)
  • generated_files - Intermediary files generated while creating SentiSynset
SentiSynset
├─── assets
| ├─── paper.pdf
| ├─── poster.pdf
| └─── slides.pdf
├─── emolex
| ├─── NRC-Emotion-Lexicon-Wordlevel-v0.92.txt
| └─── OneFilePerLanguage
| ├─── Afrikaans-NRC-EmoLex.txt
| ├─── Albanian-NRC-EmoLex.txt
| ├─── ...
| └─── Zulu-NRC-EmoLex.txt
├─── generated_files
| ├─── all_wn_translations.pkl
| ├─── lemmatized_multilingual_lexicons.pkl
| ├─── non_sentiment_normalized_lemmatized_multilingual_lexicons.pkl
| └─── normalized_lemmatized_multilingual_lexicons.pkl
├───.gitignore
├─── babelnet_conf.yml
├─── create_lexicons.py
├─── load_multingual_translations.py
├─── main.py
├─── README.md
├─── requirements.txt
├─── select_languages.pkl
├─── sentisynset_lexicon.xml
└─── translations.py

Dependencies
  • python == 3.8
  • babelnet == 1.1.0
  • langcodes == 3.4.0
  • nltk == 3.8.1
  • simplemma == 0.9.1
  • spacy == 3.7.5
  • Unidecode == 1.3.8
  • xmltodict == 0.13.0
Setup
Please ensure required packages are already installed. A virtual environment is recommended.
$ cd SentiSynset
$ pip install pip --upgrade
$ pip install -r requirements.txt
Run
The script needs to be able to read data from a local copy of the BabelNet indices (you cannot use the BabelNet API in online mode as you will quickly exceed the daily requests limit). Note that the BabelNet API requires Python 3.8.
$ python3 main.py
Authors
BibTex
@inproceedings{woudstra-etal-2024-identifying,
title = "Identifying Emotional and Polar Concepts via Synset Translation",
author = "Woudstra, Logan and Dawodu, Moyo and Igwe, Frances and Li, Senyu and Shi, Ning and Hauer, Bradley and Kondrak, Grzegorz",
editor = "Bollegala, Danushka and Shwartz, Vered",
booktitle = "Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024)",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.starsem-1.12",
pages = "142--152",
abstract = "Emotion identification and polarity classification seek to determine the sentiment expressed by a writer. Sentiment lexicons that provide classifications at the word level fail to distinguish between different senses of polysemous words. To address this problem, we propose a translation-based method for labeling each individual lexical concept and word sense. Specifically, we translate synsets into 20 different languages and verify the sentiment of these translations in multilingual sentiment lexicons. By applying our method to all WordNet synsets, we produce SentiSynset, a synset-level sentiment resource containing 12,429 emotional synsets and 15,567 polar synsets, which is significantly larger than previous resources. Experimental evaluation shows that our method outperforms prior automated methods that classify word senses, in addition to outperforming ChatGPT. We make the resulting resource publicly available on GitHub.",
}
About
This repository is for the paper Identifying Emotional and Polar Concepts via Synset Translation. In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), Mexico City, Mexico. Association for Computational Linguistics.
aclanthology.org/2024.starsem-1.12/
Topics
emotionnaaclnaacl-papernaacl2024polaritystar-semsynsettranslation
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Readme
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2 watching
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injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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SentiSynset
This repository is for the paper Identifying Emotional and Polar Concepts via Synset Translation. In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), pages 142–152, Mexico City, Mexico. Association for Computational Linguistics.
[Paper] [Poster] [Slides]
Directory
  • emolex - English and translated multingual NRC Emotion Lexicons (EmoLex)
  • generated_files - Intermediary files generated while creating SentiSynset
SentiSynset
├─── assets
| ├─── paper.pdf
| ├─── poster.pdf
| └─── slides.pdf
├─── emolex
| ├─── NRC-Emotion-Lexicon-Wordlevel-v0.92.txt
| └─── OneFilePerLanguage
| ├─── Afrikaans-NRC-EmoLex.txt
| ├─── Albanian-NRC-EmoLex.txt
| ├─── ...
| └─── Zulu-NRC-EmoLex.txt
├─── generated_files
| ├─── all_wn_translations.pkl
| ├─── lemmatized_multilingual_lexicons.pkl
| ├─── non_sentiment_normalized_lemmatized_multilingual_lexicons.pkl
| └─── normalized_lemmatized_multilingual_lexicons.pkl
├───.gitignore
├─── babelnet_conf.yml
├─── create_lexicons.py
├─── load_multingual_translations.py
├─── main.py
├─── README.md
├─── requirements.txt
├─── select_languages.pkl
├─── sentisynset_lexicon.xml
└─── translations.py

Dependencies
  • python == 3.8
  • babelnet == 1.1.0
  • langcodes == 3.4.0
  • nltk == 3.8.1
  • simplemma == 0.9.1
  • spacy == 3.7.5
  • Unidecode == 1.3.8
  • xmltodict == 0.13.0
Setup
Please ensure required packages are already installed. A virtual environment is recommended.
$ cd SentiSynset
$ pip install pip --upgrade
$ pip install -r requirements.txt
Run
The script needs to be able to read data from a local copy of the BabelNet indices (you cannot use the BabelNet API in online mode as you will quickly exceed the daily requests limit). Note that the BabelNet API requires Python 3.8.
$ python3 main.py
Authors
BibTex
@inproceedings{woudstra-etal-2024-identifying,
title = "Identifying Emotional and Polar Concepts via Synset Translation",
author = "Woudstra, Logan and Dawodu, Moyo and Igwe, Frances and Li, Senyu and Shi, Ning and Hauer, Bradley and Kondrak, Grzegorz",
editor = "Bollegala, Danushka and Shwartz, Vered",
booktitle = "Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024)",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.starsem-1.12",
pages = "142--152",
abstract = "Emotion identification and polarity classification seek to determine the sentiment expressed by a writer. Sentiment lexicons that provide classifications at the word level fail to distinguish between different senses of polysemous words. To address this problem, we propose a translation-based method for labeling each individual lexical concept and word sense. Specifically, we translate synsets into 20 different languages and verify the sentiment of these translations in multilingual sentiment lexicons. By applying our method to all WordNet synsets, we produce SentiSynset, a synset-level sentiment resource containing 12,429 emotional synsets and 15,567 polar synsets, which is significantly larger than previous resources. Experimental evaluation shows that our method outperforms prior automated methods that classify word senses, in addition to outperforming ChatGPT. We make the resulting resource publicly available on GitHub.",
}
About
This repository is for the paper Identifying Emotional and Polar Concepts via Synset Translation. In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), Mexico City, Mexico. Association for Computational Linguistics.
aclanthology.org/2024.starsem-1.12/
Topics
emotionnaaclnaacl-papernaacl2024polaritystar-semsynsettranslation
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
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} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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SentiSynset
This repository is for the paper Identifying Emotional and Polar Concepts via Synset Translation. In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), pages 142–152, Mexico City, Mexico. Association for Computational Linguistics.
[Paper] [Poster] [Slides]
Directory
  • emolex - English and translated multingual NRC Emotion Lexicons (EmoLex)
  • generated_files - Intermediary files generated while creating SentiSynset
SentiSynset
├─── assets
| ├─── paper.pdf
| ├─── poster.pdf
| └─── slides.pdf
├─── emolex
| ├─── NRC-Emotion-Lexicon-Wordlevel-v0.92.txt
| └─── OneFilePerLanguage
| ├─── Afrikaans-NRC-EmoLex.txt
| ├─── Albanian-NRC-EmoLex.txt
| ├─── ...
| └─── Zulu-NRC-EmoLex.txt
├─── generated_files
| ├─── all_wn_translations.pkl
| ├─── lemmatized_multilingual_lexicons.pkl
| ├─── non_sentiment_normalized_lemmatized_multilingual_lexicons.pkl
| └─── normalized_lemmatized_multilingual_lexicons.pkl
├───.gitignore
├─── babelnet_conf.yml
├─── create_lexicons.py
├─── load_multingual_translations.py
├─── main.py
├─── README.md
├─── requirements.txt
├─── select_languages.pkl
├─── sentisynset_lexicon.xml
└─── translations.py

Dependencies
  • python == 3.8
  • babelnet == 1.1.0
  • langcodes == 3.4.0
  • nltk == 3.8.1
  • simplemma == 0.9.1
  • spacy == 3.7.5
  • Unidecode == 1.3.8
  • xmltodict == 0.13.0
Setup
Please ensure required packages are already installed. A virtual environment is recommended.
$ cd SentiSynset
$ pip install pip --upgrade
$ pip install -r requirements.txt
Run
The script needs to be able to read data from a local copy of the BabelNet indices (you cannot use the BabelNet API in online mode as you will quickly exceed the daily requests limit). Note that the BabelNet API requires Python 3.8.
$ python3 main.py
Authors
BibTex
@inproceedings{woudstra-etal-2024-identifying,
title = "Identifying Emotional and Polar Concepts via Synset Translation",
author = "Woudstra, Logan and Dawodu, Moyo and Igwe, Frances and Li, Senyu and Shi, Ning and Hauer, Bradley and Kondrak, Grzegorz",
editor = "Bollegala, Danushka and Shwartz, Vered",
booktitle = "Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024)",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.starsem-1.12",
pages = "142--152",
abstract = "Emotion identification and polarity classification seek to determine the sentiment expressed by a writer. Sentiment lexicons that provide classifications at the word level fail to distinguish between different senses of polysemous words. To address this problem, we propose a translation-based method for labeling each individual lexical concept and word sense. Specifically, we translate synsets into 20 different languages and verify the sentiment of these translations in multilingual sentiment lexicons. By applying our method to all WordNet synsets, we produce SentiSynset, a synset-level sentiment resource containing 12,429 emotional synsets and 15,567 polar synsets, which is significantly larger than previous resources. Experimental evaluation shows that our method outperforms prior automated methods that classify word senses, in addition to outperforming ChatGPT. We make the resulting resource publicly available on GitHub.",
}
About
This repository is for the paper Identifying Emotional and Polar Concepts via Synset Translation. In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), Mexico City, Mexico. Association for Computational Linguistics.
aclanthology.org/2024.starsem-1.12/
Topics
emotionnaaclnaacl-papernaacl2024polaritystar-semsynsettranslation
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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SentiSynset
This repository is for the paper Identifying Emotional and Polar Concepts via Synset Translation. In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), pages 142–152, Mexico City, Mexico. Association for Computational Linguistics.
[Paper] [Poster] [Slides]
Directory
  • emolex - English and translated multingual NRC Emotion Lexicons (EmoLex)
  • generated_files - Intermediary files generated while creating SentiSynset
SentiSynset
├─── assets
| ├─── paper.pdf
| ├─── poster.pdf
| └─── slides.pdf
├─── emolex
| ├─── NRC-Emotion-Lexicon-Wordlevel-v0.92.txt
| └─── OneFilePerLanguage
| ├─── Afrikaans-NRC-EmoLex.txt
| ├─── Albanian-NRC-EmoLex.txt
| ├─── ...
| └─── Zulu-NRC-EmoLex.txt
├─── generated_files
| ├─── all_wn_translations.pkl
| ├─── lemmatized_multilingual_lexicons.pkl
| ├─── non_sentiment_normalized_lemmatized_multilingual_lexicons.pkl
| └─── normalized_lemmatized_multilingual_lexicons.pkl
├───.gitignore
├─── babelnet_conf.yml
├─── create_lexicons.py
├─── load_multingual_translations.py
├─── main.py
├─── README.md
├─── requirements.txt
├─── select_languages.pkl
├─── sentisynset_lexicon.xml
└─── translations.py

Dependencies
  • python == 3.8
  • babelnet == 1.1.0
  • langcodes == 3.4.0
  • nltk == 3.8.1
  • simplemma == 0.9.1
  • spacy == 3.7.5
  • Unidecode == 1.3.8
  • xmltodict == 0.13.0
Setup
Please ensure required packages are already installed. A virtual environment is recommended.
$ cd SentiSynset
$ pip install pip --upgrade
$ pip install -r requirements.txt
Run
The script needs to be able to read data from a local copy of the BabelNet indices (you cannot use the BabelNet API in online mode as you will quickly exceed the daily requests limit). Note that the BabelNet API requires Python 3.8.
$ python3 main.py
Authors
BibTex
@inproceedings{woudstra-etal-2024-identifying,
title = "Identifying Emotional and Polar Concepts via Synset Translation",
author = "Woudstra, Logan and Dawodu, Moyo and Igwe, Frances and Li, Senyu and Shi, Ning and Hauer, Bradley and Kondrak, Grzegorz",
editor = "Bollegala, Danushka and Shwartz, Vered",
booktitle = "Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024)",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.starsem-1.12",
pages = "142--152",
abstract = "Emotion identification and polarity classification seek to determine the sentiment expressed by a writer. Sentiment lexicons that provide classifications at the word level fail to distinguish between different senses of polysemous words. To address this problem, we propose a translation-based method for labeling each individual lexical concept and word sense. Specifically, we translate synsets into 20 different languages and verify the sentiment of these translations in multilingual sentiment lexicons. By applying our method to all WordNet synsets, we produce SentiSynset, a synset-level sentiment resource containing 12,429 emotional synsets and 15,567 polar synsets, which is significantly larger than previous resources. Experimental evaluation shows that our method outperforms prior automated methods that classify word senses, in addition to outperforming ChatGPT. We make the resulting resource publicly available on GitHub.",
}
About
This repository is for the paper Identifying Emotional and Polar Concepts via Synset Translation. In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), Mexico City, Mexico. Association for Computational Linguistics.
aclanthology.org/2024.starsem-1.12/
Topics
emotionnaaclnaacl-papernaacl2024polaritystar-semsynsettranslation
Resources
Readme
Activity
Custom properties
Stars
0 stars
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors
Languages