Text Classification of Flu-related Tweets Using FastText with Sentiment and Keyword Features

被引：12

作者：

Alessa, Ali ^{[1
]}

Faezipour, Miad ^{[1
,2
]}

Alhassan, Zakhriya ^{[3
]}

机构：

[1] Univ Bridgeport, Comp Sci & Engn Dept, Sch Engn, Bridgeport, CT 06601 USA

[2] Univ Bridgeport, Biomed Engn Dept, Sch Engn, Bridgeport, CT USA

[3] Univ Durham, Comp Sci Dept, Sch Engn & Comp Sci, Durham, England

来源：

2018 IEEE INTERNATIONAL CONFERENCE ON HEALTHCARE INFORMATICS (ICHI) | 2018年

关键词：

fastText; flu tweet classification; topic-related-keywords; sentiment; Social Networking Site;

D O I：

10.1109/ICHI.2018.00058

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this study, we present a framework for flu-prediction/detection based on the available data of Social Networking Sites (SNS). The framework uses a state-of-the-art text classifier, which is FastText, to classify Twitter posts into flu-related or flu-unrelated posts. The FastText based framework is trained and tested using a pre-labeled dataset and utilizing the features of sentiment analysis and predefined keyword occurrences in addition to textual features. Results show that the framework improves the accuracy, in addition to the efficiency of flu disease surveillance systems that use unstructured data such as posts of Social Networking Sites.

引用

页码：366 / 367

页数：2

共 50 条

[1] Sentiment Classification of Crisis Related Tweets using Segmentation
Lalrempuii, Candy
Mittal, Namita
[J]. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INFORMATICS AND ANALYTICS (ICIA' 16), 2016,
[2] Sentiment Classification of Tweets using Hierarchical Classification
Baqapuri, Afroze Ibrahim
Saleh, Saad
Ilyas, Muhammad U.
Khan, Muhammad Murtaza
Qamar, Ali Mustafa
[J]. 2016 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2016,
[3] TEXT CLASSIFICATION FOR SUICIDE RELATED TWEETS
Chiroma, Fatima
Liu, Han
Cocea, Mihaela
[J]. PROCEEDINGS OF 2018 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS (ICMLC), VOL 2, 2018, : 587 - 592
[4] Sentiment Classification of Tweets with Non-Language Features
Akilandeswari, J.
Jothi, G.
[J]. 8TH INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING & COMMUNICATIONS (ICACC-2018), 2018, 143 : 426 - 433
[5] A Comparison of fastText Implementations Using Arabic Text Classification
Alghamdi, Nuha
Assiri, Fatmah
[J]. INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 2, 2020, 1038 : 306 - 311
[6] Sentiment Classification Using fastText Embedding and Deep Learning Model
Khasanah, Isnaini Nurul
[J]. AI IN COMPUTATIONAL LINGUISTICS, 2021, 189 : 343 - 350
[7] Medical-Based Text Classification Using FastText Features and CNN-LSTM Model
Zeghdaoui, Mohamed Walid
Boussaid, Omar
Bentayeb, Fadila
Joly, Frederik
[J]. DATABASE AND EXPERT SYSTEMS APPLICATIONS, DEXA 2021, PT I, 2021, 12923 : 155 - 167
[8] Sentiment analysis using various machine learning algorithms for disaster related tweets classification
Sudha, S. Baby
Dhanalakshmi, S.
[J]. INTERNATIONAL JOURNAL OF INTELLIGENT ENGINEERING INFORMATICS, 2023, 11 (04) : 390 - 417
[9] Sentiment polarity classification of tweets using an extended dictionary
Vargas-Calderon, Vladimir
Vargas Sanchez, Nelson A.
Calderon-Benavides, Liliana
Camargo, Jorge E.
[J]. INTELIGENCIA ARTIFICIAL-IBEROAMERICAL JOURNAL OF ARTIFICIAL INTELLIGENCE, 2018, 21 (62): : 1 - 11
[10] ENHANCED SENTIMENT CLASSIFICATION USING GEO LOCATION TWEETS
Phand, Shital Anil
Chakkarwar, V. A.
[J]. PROCEEDINGS OF THE 2018 SECOND INTERNATIONAL CONFERENCE ON INVENTIVE COMMUNICATION AND COMPUTATIONAL TECHNOLOGIES (ICICCT), 2018, : 881 - 886

← 1 2 3 4 5 →