A geofencing-based recent trends identification from twitter data
For facilitating users from information overloading by finding recent trends in twitter, several techniques are proposed. However, most of these techniques need to process extensive data. Therefore, in this paper, a geofencing-based recent trends identification technique is proposed, which acquires...
| Main Authors: | , , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IOP Publishing
2020
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/28788/1/A%20geofencing-based%20recent%20trends%20identification%20from%20twitter%20data.pdf |
| _version_ | 1796994138052231168 |
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| author | M., Saef Ullah Miah M., Sadid Tahsin Azad, Saiful Rabby, Gollam M., Sirajul Islam Uddin, Shihab M., Masuduzzaman |
| author_facet | M., Saef Ullah Miah M., Sadid Tahsin Azad, Saiful Rabby, Gollam M., Sirajul Islam Uddin, Shihab M., Masuduzzaman |
| author_sort | M., Saef Ullah Miah |
| collection | UMP |
| description | For facilitating users from information overloading by finding recent trends in twitter, several techniques are proposed. However, most of these techniques need to process extensive data. Therefore, in this paper, a geofencing-based recent trends identification technique is proposed, which acquires data based on a geofence. Afterwards, they are cleaned and the weight of these tweet data is calculated. For that, the frequency of tweet texts and hashtags are taken into account along with a boosting factor. Thereafter, they are ranked to recommend recent trends to the user. This proposed technique is applied in developing a system using Java and python. It is compared with other relevant systems, where it demonstrates that the performance of the proposed system is comparable. Over and above, since the proposed system integrates geofencing feature, it is more preferable over other systems. |
| first_indexed | 2024-03-06T12:43:40Z |
| format | Conference or Workshop Item |
| id | UMPir28788 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T12:43:40Z |
| publishDate | 2020 |
| publisher | IOP Publishing |
| record_format | dspace |
| spelling | UMPir287882022-06-20T03:02:04Z http://umpir.ump.edu.my/id/eprint/28788/ A geofencing-based recent trends identification from twitter data M., Saef Ullah Miah M., Sadid Tahsin Azad, Saiful Rabby, Gollam M., Sirajul Islam Uddin, Shihab M., Masuduzzaman QA Mathematics QA76 Computer software For facilitating users from information overloading by finding recent trends in twitter, several techniques are proposed. However, most of these techniques need to process extensive data. Therefore, in this paper, a geofencing-based recent trends identification technique is proposed, which acquires data based on a geofence. Afterwards, they are cleaned and the weight of these tweet data is calculated. For that, the frequency of tweet texts and hashtags are taken into account along with a boosting factor. Thereafter, they are ranked to recommend recent trends to the user. This proposed technique is applied in developing a system using Java and python. It is compared with other relevant systems, where it demonstrates that the performance of the proposed system is comparable. Over and above, since the proposed system integrates geofencing feature, it is more preferable over other systems. IOP Publishing 2020-06-05 Conference or Workshop Item PeerReviewed pdf en cc_by http://umpir.ump.edu.my/id/eprint/28788/1/A%20geofencing-based%20recent%20trends%20identification%20from%20twitter%20data.pdf M., Saef Ullah Miah and M., Sadid Tahsin and Azad, Saiful and Rabby, Gollam and M., Sirajul Islam and Uddin, Shihab and M., Masuduzzaman (2020) A geofencing-based recent trends identification from twitter data. In: IOP Conference Series: Materials Science and Engineering, 6th International Conference on Software Engineering and Computer Systems (ICSECS 2019) , 25 - 27 September 2019 , Vistana Kuantan City Center, Kuantan, Pahang. pp. 1-10., 769 (012008). ISSN 1757-8981 (Print), 1757-899X (Online) https://doi.org/10.1088/1757-899X/769/1/012008 |
| spellingShingle | QA Mathematics QA76 Computer software M., Saef Ullah Miah M., Sadid Tahsin Azad, Saiful Rabby, Gollam M., Sirajul Islam Uddin, Shihab M., Masuduzzaman A geofencing-based recent trends identification from twitter data |
| title | A geofencing-based recent trends identification from twitter data |
| title_full | A geofencing-based recent trends identification from twitter data |
| title_fullStr | A geofencing-based recent trends identification from twitter data |
| title_full_unstemmed | A geofencing-based recent trends identification from twitter data |
| title_short | A geofencing-based recent trends identification from twitter data |
| title_sort | geofencing based recent trends identification from twitter data |
| topic | QA Mathematics QA76 Computer software |
| url | http://umpir.ump.edu.my/id/eprint/28788/1/A%20geofencing-based%20recent%20trends%20identification%20from%20twitter%20data.pdf |
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