A Novel Approach for Detection of Fake News on Social Media Using Metaheuristic Optimization Algorithms
Deceptive content is becoming increasingly dangerous, such as fake news created by social media users. Individuals and society have been affected negatively by the spread of low-quality news on social media. The fake and real news needs to be detected to eliminate the disadvantages of social media....
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Kaunas University of Technology
2019-08-01
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| Series: | Elektronika ir Elektrotechnika |
| Subjects: | |
| Online Access: | http://eejournal.ktu.lt/index.php/elt/article/view/23972 |
| _version_ | 1819071677837869056 |
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| author | Feyza Altunbey Ozbay Bilal Alatas |
| author_facet | Feyza Altunbey Ozbay Bilal Alatas |
| author_sort | Feyza Altunbey Ozbay |
| collection | DOAJ |
| description | Deceptive content is becoming increasingly dangerous, such as fake news created by social media users. Individuals and society have been affected negatively by the spread of low-quality news on social media. The fake and real news needs to be detected to eliminate the disadvantages of social media. This paper proposes a novel approach for fake news detection (FND) problem on social media. Applying this approach, FND problem has been considered as an optimization problem for the first time and two metaheuristic algorithms, the Grey Wolf Optimization (GWO) and Salp Swarm Optimization (SSO) have been adapted to the FND problem for the first time as well. The proposed FND approach consists of three stages. The first stage is data preprocessing. The second stage is adapting GWO and SSO for construction of a novel FND model. The last stage consists of using proposed FND model for testing. The proposed approach has been evaluated using three different real-world datasets. The results have been compared with seven supervised artificial intelligence algorithms. The results show GWO algorithm has the best performance in comparison with SSO algorithm and the other artificial intelligence algorithms. GWO seems to be efficiently used for solving different types of social media problems. |
| first_indexed | 2024-12-21T17:25:38Z |
| format | Article |
| id | doaj.art-36699af8f6d1413899df7cc6809cde2c |
| institution | Directory Open Access Journal |
| issn | 1392-1215 2029-5731 |
| language | English |
| last_indexed | 2024-12-21T17:25:38Z |
| publishDate | 2019-08-01 |
| publisher | Kaunas University of Technology |
| record_format | Article |
| series | Elektronika ir Elektrotechnika |
| spelling | doaj.art-36699af8f6d1413899df7cc6809cde2c2022-12-21T18:56:03ZengKaunas University of TechnologyElektronika ir Elektrotechnika1392-12152029-57312019-08-01254626710.5755/j01.eie.25.4.2397223972A Novel Approach for Detection of Fake News on Social Media Using Metaheuristic Optimization AlgorithmsFeyza Altunbey OzbayBilal AlatasDeceptive content is becoming increasingly dangerous, such as fake news created by social media users. Individuals and society have been affected negatively by the spread of low-quality news on social media. The fake and real news needs to be detected to eliminate the disadvantages of social media. This paper proposes a novel approach for fake news detection (FND) problem on social media. Applying this approach, FND problem has been considered as an optimization problem for the first time and two metaheuristic algorithms, the Grey Wolf Optimization (GWO) and Salp Swarm Optimization (SSO) have been adapted to the FND problem for the first time as well. The proposed FND approach consists of three stages. The first stage is data preprocessing. The second stage is adapting GWO and SSO for construction of a novel FND model. The last stage consists of using proposed FND model for testing. The proposed approach has been evaluated using three different real-world datasets. The results have been compared with seven supervised artificial intelligence algorithms. The results show GWO algorithm has the best performance in comparison with SSO algorithm and the other artificial intelligence algorithms. GWO seems to be efficiently used for solving different types of social media problems.http://eejournal.ktu.lt/index.php/elt/article/view/23972classification algorithmsdata analysisoptimization methodstext mining |
| spellingShingle | Feyza Altunbey Ozbay Bilal Alatas A Novel Approach for Detection of Fake News on Social Media Using Metaheuristic Optimization Algorithms Elektronika ir Elektrotechnika classification algorithms data analysis optimization methods text mining |
| title | A Novel Approach for Detection of Fake News on Social Media Using Metaheuristic Optimization Algorithms |
| title_full | A Novel Approach for Detection of Fake News on Social Media Using Metaheuristic Optimization Algorithms |
| title_fullStr | A Novel Approach for Detection of Fake News on Social Media Using Metaheuristic Optimization Algorithms |
| title_full_unstemmed | A Novel Approach for Detection of Fake News on Social Media Using Metaheuristic Optimization Algorithms |
| title_short | A Novel Approach for Detection of Fake News on Social Media Using Metaheuristic Optimization Algorithms |
| title_sort | novel approach for detection of fake news on social media using metaheuristic optimization algorithms |
| topic | classification algorithms data analysis optimization methods text mining |
| url | http://eejournal.ktu.lt/index.php/elt/article/view/23972 |
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