Kernel Metadata Declaration — on demand
ISO 26324 asks a DOI Registration Agency to produce a Kernel Metadata Declaration for every DOI it issues. Give any DOI: its public record becomes a record in the Smart Scholars DOI Metadata Format 1.0, checked against every rule, and declared as the Kernel XML.
✓ Meets every rule of the format
The record below is complete and every controlled value is a DOI Attribute Value Set 2.3 spelling. The Declaration on the right follows DOIMetadataKernel.xsd element by element.
What the DOI identifies
SARCAMNET: EXTENSION OF LEXICON ALGORITHM FOR EMOJI-BASED SARCASM DETECTION FROM TWITTER DATA
10.46243/jst.2024.v9.i01.pp116-124 · JournalArticle — an article in a journal · Digital · Visual · Language · en
Published 2024-01-25
Part of Journal of Science & Technology · ISSN 2456-5660 · vol. 9 · no. 1 · pp. 116–124
Principal agents
- Dr.SUBBA REDDY BORRA Dr.SUBBA REDDY BORRA (author → Author)
- Longman Publishers (publisher → Publisher)
Also in the record, outside the Kernel: the abstract, the licence, 3 links, 24 references. Source: Crossref (member 25296), registered 2024-02-16, last deposited 2026-09-17.
System metadata — ISO 26324:2025, Annex B · DOI Handbook 10.1
Each element by the standard's name and the Handbook's (in grey), read off the record.
| DOI Name DOI name | 10.46243/jst.2024.v9.i01.pp116-124 |
| Referent Type referentType | Creation |
| Referent Sub-Type referentSubType | JournalArticle — an article in a journal |
| Referent Name(s) referentName(s) | SARCAMNET: EXTENSION OF LEXICON ALGORITHM FOR EMOJI-BASED SARCASM DETECTION FROM TWITTER DATA (PrincipalTitle, en) |
| Basic Metadata basicMetadata | author: Dr.SUBBA REDDY BORRA Dr.SUBBA REDDY BORRA publisher: Longman Publishers published: 2024-01-25 part of: Journal of Science & Technology · ISSN 2456-5660 · vol. 9 · no. 1 · pp. 116–124 language: en form: Digital · Visual · Language |
| Referent Identifier(s) alternateIdentifier(s) | none besides the DOI |
| Registration Authority registrationAuthorityCode | Crossref — issued by Crossref (member 25296); held here as a copy |
| Created Date issueDate | 2024-02-16 |
| relatedIdentifiers | none needed — the descriptive metadata is in this record |
The record
{
"format": "smartscholars-doi-metadata/1.0",
"doi": "10.46243/jst.2024.v9.i01.pp116-124",
"referent": "Creation",
"type": "JournalArticle",
"structural_type": "Digital",
"modes": [
"Visual"
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"characters": [
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"titles": [
{
"value": "SARCAMNET: EXTENSION OF LEXICON ALGORITHM FOR EMOJI-BASED SARCASM DETECTION FROM TWITTER DATA",
"type": "PrincipalTitle",
"lang": "en"
}
],
"identifiers": [
{
"type": "DOI",
"value": "10.46243/jst.2024.v9.i01.pp116-124"
}
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"agents": [
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"role": "author",
"name": {
"given": "Dr.SUBBA REDDY BORRA",
"family": "Dr.SUBBA REDDY BORRA"
},
"sequence": "first"
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{
"role": "publisher",
"name": {
"org": "Longman Publishers"
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"dates": {
"published": "2024-01-25",
"date_type": "PublicationDate",
"online": "2024-01-25"
},
"language": "en",
"container": {
"type": "Journal",
"titles": [
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"type": "PrincipalTitle"
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"identifiers": [
{
"type": "ISSN",
"value": "2456-5660",
"medium": "electronic"
}
],
"volume": "9",
"issue": "1",
"pages": {
"first": "116",
"last": "124"
}
},
"links": [
{
"url": "https://www.jst.org.in/index.php/pub/article/view/32",
"return_type": "text/html",
"primary": true
},
{
"url": "https://www.jst.org.in/index.php/pub/article/download/32/25",
"purpose": "text-mining",
"return_type": "application/pdf"
},
{
"url": "https://www.jst.org.in/index.php/pub/article/download/32/1478",
"purpose": "text-mining",
"return_type": "application/xml"
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],
"abstract": {
"value": "Lexicon algorithm is used to determine the sentiment expressed by a textual content. This sentiment might be negative, neutral, or positive. It is possible to be sarcastic using only positive or neutral sentiment textual contents. Hence, lexicon algorithm can be useful but insufficient for sarcasm detection. It is necessary to extend the lexicon algorithm to come up with systems that would be proven efficient for sarcasm detection on neutral and positive sentiment textual contents. In this paper, two sarcasm analysis systems both obtained from the extension of the lexicon algorithm have been proposed for that sake. The first system consists of the combination of a lexicon algorithm and a pure sarcasm analysis algorithm. The second system consists of the combination of a lexicon algorithm and a sentiment prediction algorithm. Finally, naive bayes are used to predict sarcasm detection using pretrained features.",
"lang": "en"
},
"license": {
"url": "https://creativecommons.org/licenses/by/4.0",
"start": "2024-01-25",
"applies_to": "vor"
},
"references": [
{
"key": "ref1",
"unstructured": "Cambridge University Press, 2023. Sarcasm. [Online] Available At: Https://Dictionary. Cambridge.Org/Dictionary/English/Sarc Asm [Accessed 20 January 2018]"
},
{
"key": "ref2",
"unstructured": "Palanisamy, P., Yadav, V., & Elchuri, H. (2023). Serendio: Simple And Practical Lexicon-Based Approach To Sentiment. 543-548"
},
{
"key": "ref3",
"doi": "10.1186/s13388-015-0024-x",
"unstructured": "Jurek, A., Mulvenna, M. D., & Bi, Y. (2021). Improved Lexicon-Based Sentiment Analysis For Social Media Analytics. Springeropen, 4-9"
},
{
"key": "ref4",
"doi": "10.29322/ijsrp.8.3.2018.p7517",
"unstructured": "Kiilu, K. K., Okeyo, G., Rimiru, R., & Ogada, K. (2022). Using Naïve Bayes Algorithm In Detection Of Hate Tweets. International Journal Of Scientific And Research Publications, 99-"
},
{
"key": "ref5",
"unstructured": "Rathan, K., & Suchithra, R. (2022). Sarcasm Detection Using Combinational. Imperial Journal Of Interdisciplinary Research, 546-551"
},
{
"key": "ref6",
"doi": "10.14569/ijarai.2013.020206",
"unstructured": "Sathya, R., & Abraham, A. (2022). Comparison Of Supervised And Unsupervised. International Journal Of Advanced Research In Artificial Intelligence, 34-38"
},
{
"key": "ref7",
"unstructured": "Dataquest, 2022. Top 10 Machine Learning Algorithms For Beginners. [Online] Available At: <Https://Www.Dataquest.Io/Blog/Top-10-Machine-Learning-Algorithms-For-Beginners/> [Accessed 15 September 2022]"
},
{
"key": "ref8",
"unstructured": "Haripriya, V., & Patil, D. P. (2022). A Survey Of Sarcasm Detection In Social Media. International Journal For Research In Applied Science & Engineering Technology, 1748-1753"
},
{
"key": "ref9",
"unstructured": "Musto, C., Semeraro, G., & Polignano, M. (n.d.). A Comparison Of Lexicon-Based Approaches For Sentiment Analysis Of Microblog Posts. Figure 1. System Architecture RESULT Above screen descibes sarcasm result based on input dataset. Above screen discribed sarcasm content like positive and nagetive. CONCLUSION The aim of this study was to propose ways to extend the lexicon algorithm to build systems that would be Dr. SUBBA REDDY BORRA, T. KRUTHIKA, T.SAI POOJITHA, P. DEEPIKA: SARCAMNET: EXTENSION OF LEXICON ALGORITHM FOR EMOJI-BASED SARCASM DETECTION FROM TWITTER DATA"
},
{
"key": "ref10",
"unstructured": "Saxena, R., 2023. How The Naive Bayes Classifier Works In Machine Learning. [Online] Available At: Http://Dataaspirant.Com/2023/02/06/ Naivebayes-Classifier-Machine-Learning/ [Accessed 10 February 2023]"
},
{
"key": "ref11",
"unstructured": "Gandhi, R., 2022. Naive Bayes Classifier. [Online] Available At: Https://Towardsdatascience.Com/ Naivebayes-Classifier-81d512f50a7c [Accessed 10 February 2023]"
},
{
"key": "ref12",
"unstructured": "Ray, S., 2023. 6 Easy Steps To Learn Naive Bayes Algorithm (With Codes In Python And R). [Online] Available At: Https://Www.Analyticsvidhya. Com/Blog/2023/09/Naivebayesexplained/ [Accessed 10 February 2023]"
},
{
"key": "ref13",
"unstructured": "Aggarwal, S., & Kaur, D. (2023). Naïve Bayes Classifier With Various Smoothing. International Journal Of Computer Trends And Technology, 873-876"
},
{
"key": "ref14",
"unstructured": "Subba Reddy Borra, G. Jagadeeswar Reddy And E. Sreenivasa Reddy, “Fingerprint Image Compression Using Wave Atom Transform”, International Journal Of Advanced Computing, Vol. 48, No. 1, 2015"
},
{
"key": "ref15",
"doi": "10.1016/j.aci.2017.07.001",
"unstructured": "Subba Reddyborra, G.Jagadeeswar Reddy, E.Sreenivasa Reddy, “Classification Of Fingerprint Images With The Aid Of Morphological Operation And Agnn Classifier”, Applied Computing And Informatics, 2017"
},
{
"key": "ref16",
"unstructured": "Subba Reddy Borra, Akshaya, B. Swathi, B. Sraveena, B. Satya Sahithi. (2023). Machine Learning Algorithms-Based Prediction Of Botnet Attack For Iot Devices. Turkish Journal Of Computer And Mathematics Education (Turcomat), 14(03), 65–78. Https://Doi. Org/10.17762/Turcomat.v14i03.13938"
},
{
"key": "ref17",
"unstructured": "Dr. B. Subba Reddy, D. R. Amrutha Nayana, G. Sahaja, G. Shanmukha Priya. (2023). Artificial Intelligence Tool For Fake Account Detection From Online Social Networks. Turkish Journal Of Computer And Mathematics Education (Turcomat), 14(1), 243–254. Https://Doi. Org/10.17762/Turcomat.v14i1.13528"
},
{
"key": "ref18",
"unstructured": "Subba Reddy Borra, B Gayathri, B Rekha, B Akshitha, B. Hafeeza. (2023). K-Nearest Neighbour Classifier For Url-Based Phishing Detection Mechanism. Turkish Journal Of Computer And Mathematics Education (Turcomat), 14(03), 34–40. Https://Doi. Org/10.17762/Turcomat.v14i03.13935"
},
{
"key": "ref19",
"unstructured": "Dr. Subba Reddy Borra, K.Harshitha, Kudithi Neha, K. Sindhusha, K. Akshaya. (2023). Block Chain Based Agriculture Crop Delivery Platform For Enforcing Transparency. Turkish Journal Of Computer And Mathematics Education (Turcomat), 14(2), 987–997. Https://Doi. Org/10.17762/Turcomat.v14i2.13925"
},
{
"key": "ref20",
"doi": "10.61841/turcomat.v14i03.14521",
"unstructured": "Dr. B. Subba Reddy, S. Shresta, S. Sathhvika, P. Lakshmi Manasa Shreya. (2023). Detection Of Electricity Theft Cyber-Attacks In Renewable Distributed Generation For Future Iot-Based Smart Electric Meters. Turkish Journal Of Computer And Mathematics Education (Turcomat), 14(2), 64–77. Https://Doi. Org/10.17762/Turcomat.v14i2.13523"
},
{
"key": "ref21",
"unstructured": "Dr. Subba Reddy Borra, K.Harshitha, Kudithi Neha, K. Sindhusha, K. Akshaya. (2023). Block Chain Based Agriculture Crop Delivery Platform For Enforcing Transparency. Turkish Journal Of Computer And Mathematics Education (Turcomat), 14(2), 987–997. Https://Doi. Org/10.17762/Turcomat.v14i2.13925"
},
{
"key": "ref22",
"doi": "10.17762/turcomat.v12i2.2351",
"unstructured": "Dr. B. Subba Reddy, S. Shresta, S. Sathhvika, P. Lakshmi Manasa Shreya. (2022). Role Of Machine Learning In Education: Performance Tracking And Prediction Of Students. Turkish Journal Of Computer And Mathematics Education (Turcomat), 13(03), 854–862. Https://Doi. Org/10.17762/Turcomat.v13i03.13175"
},
{
"key": "ref23",
"unstructured": "B. Subba Reddy, V. Bhargavi., S. Samhitha, Y. Anjana, V. Saivaishnavi. (2023). Nlp-Based Supervised Learning Algorithm For Cyber Insurance Policy Pattern Prediction. Turkish Journal Of Computer And Mathematics Education (Turcomat), 14(03), 90–99. Https:// Doi.Org/10.17762/Turcomat.v14i03.13941"
},
{
"key": "ref24",
"unstructured": "Dr. B. Subba Reddy, P. Sai Hamshika, S. Aishwarya, V. Ashritha. (2022). Block Chain For Financial Application Using Iot. Turkish Journal Of Computer And Mathematics Education (Turcomat), 13(03), 844–853. Https://Doi. Org/10.17762/Turcomat.v13i03.13174"
}
],
"record": {
"registrant": "Longman Publishers",
"registered": "2024-02-16",
"updated": "2026-09-17",
"issue_number": 1,
"source": "crossref-api",
"source_agency": "Crossref (member 25296)"
}
}The Kernel Metadata Declaration
DOIMetadataKernel.xsd · namespace http://www.doi.org/2010/DOISchema · Attribute Value Sets 2.3 · draft — the agency's DOI name is filled in on accreditation
<?xml version="1.0" encoding="UTF-8"?>
<!-- DRAFT declaration: Smart Scholars is not yet a DOI Registration Agency. registrationAgencyDoiName is a marker (10.0/ is no RA's prefix) and is filled in on accreditation. -->
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<identifier>
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<type>URI</type>
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