Identify the Subject and Content of Tweets on Twitter Using Multilayer Neural Network Method and Random Graphs
The result of the research is a proposed model for text analysis and identifying the subject and content of texts on Twitter. In this model, two main phases are implemented for classification. In text mining problems and in text mining tasks in general, because the data used is unstructured text, th...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Iran Telecom Research Center
2023-02-01
|
| Series: | International Journal of Information and Communication Technology Research |
| Subjects: | |
| Online Access: | http://ijict.itrc.ac.ir/article-1-510-en.pdf |
| _version_ | 1827889434380468224 |
|---|---|
| author | Vahid Yazdanian Mohsen Gerami Mohammad Sadeghinia |
| author_facet | Vahid Yazdanian Mohsen Gerami Mohammad Sadeghinia |
| author_sort | Vahid Yazdanian |
| collection | DOAJ |
| description | The result of the research is a proposed model for text analysis and identifying the subject and content of texts on Twitter. In this model, two main phases are implemented for classification. In text mining problems and in text mining tasks in general, because the data used is unstructured text, there is a preprocessing phase to extract the feature from this unstructured data. Done. In the second phase of the proposed method, a multilayer neural network algorithm and random graphs are used to classify the texts. In fact, this algorithm is a method for classifying a text based on the training model. The results show a significant improvement. Comparing the proposed method with other methods, according to the results, we found that the proposed algorithm has a high percentage of improvement in accuracy and has a better performance than other methods. All the presented statistics and simulation output results of the proposed method are based on the implementation in MATLAB software. |
| first_indexed | 2024-03-12T20:55:36Z |
| format | Article |
| id | doaj.art-f0ea4e7463f846d5a88b61b01a3e1916 |
| institution | Directory Open Access Journal |
| issn | 2251-6107 2783-4425 |
| language | English |
| last_indexed | 2024-03-12T20:55:36Z |
| publishDate | 2023-02-01 |
| publisher | Iran Telecom Research Center |
| record_format | Article |
| series | International Journal of Information and Communication Technology Research |
| spelling | doaj.art-f0ea4e7463f846d5a88b61b01a3e19162023-07-31T18:22:53ZengIran Telecom Research CenterInternational Journal of Information and Communication Technology Research2251-61072783-44252023-02-011512434Identify the Subject and Content of Tweets on Twitter Using Multilayer Neural Network Method and Random GraphsVahid Yazdanian0Mohsen Gerami1Mohammad Sadeghinia2 ICT Research Institute (ITRC) Tehran, Iran ICT Research Institute (ITRC) Tehran, Iran Mohammad Sadeghinia Science and Research Branch Islamic Azad University Tehran, Iran The result of the research is a proposed model for text analysis and identifying the subject and content of texts on Twitter. In this model, two main phases are implemented for classification. In text mining problems and in text mining tasks in general, because the data used is unstructured text, there is a preprocessing phase to extract the feature from this unstructured data. Done. In the second phase of the proposed method, a multilayer neural network algorithm and random graphs are used to classify the texts. In fact, this algorithm is a method for classifying a text based on the training model. The results show a significant improvement. Comparing the proposed method with other methods, according to the results, we found that the proposed algorithm has a high percentage of improvement in accuracy and has a better performance than other methods. All the presented statistics and simulation output results of the proposed method are based on the implementation in MATLAB software.http://ijict.itrc.ac.ir/article-1-510-en.pdftext miningsubject and content recognitionmultilayer neural networkrandom graphstwitter |
| spellingShingle | Vahid Yazdanian Mohsen Gerami Mohammad Sadeghinia Identify the Subject and Content of Tweets on Twitter Using Multilayer Neural Network Method and Random Graphs International Journal of Information and Communication Technology Research text mining subject and content recognition multilayer neural network random graphs |
| title | Identify the Subject and Content of Tweets on Twitter Using Multilayer Neural Network Method and Random Graphs |
| title_full | Identify the Subject and Content of Tweets on Twitter Using Multilayer Neural Network Method and Random Graphs |
| title_fullStr | Identify the Subject and Content of Tweets on Twitter Using Multilayer Neural Network Method and Random Graphs |
| title_full_unstemmed | Identify the Subject and Content of Tweets on Twitter Using Multilayer Neural Network Method and Random Graphs |
| title_short | Identify the Subject and Content of Tweets on Twitter Using Multilayer Neural Network Method and Random Graphs |
| title_sort | identify the subject and content of tweets on twitter using multilayer neural network method and random graphs |
| topic | text mining subject and content recognition multilayer neural network random graphs |
| url | http://ijict.itrc.ac.ir/article-1-510-en.pdf |
| work_keys_str_mv | AT vahidyazdanian identifythesubjectandcontentoftweetsontwitterusingmultilayerneuralnetworkmethodandrandomgraphs AT mohsengerami identifythesubjectandcontentoftweetsontwitterusingmultilayerneuralnetworkmethodandrandomgraphs AT mohammadsadeghinia identifythesubjectandcontentoftweetsontwitterusingmultilayerneuralnetworkmethodandrandomgraphs |