Analysis of Persian News Agencies on Instagram, A Words Co-occurrence Graph-based Approach
The rise of the Internet and the exponential increase in data have made manual data summarization and analysis a challenging task. Instagram social network is a prominent social network widely utilized in Iran for information sharing and communication across various age groups. The inherent structur...
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University of science and culture
2023-01-01
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| Series: | International Journal of Web Research |
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| Online Access: | https://ijwr.usc.ac.ir/article_186781_de5edc5627e528914c1cff42c47b1693.pdf |
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| author | Mohammad Heydari Babak Teimourpour |
| author_facet | Mohammad Heydari Babak Teimourpour |
| author_sort | Mohammad Heydari |
| collection | DOAJ |
| description | The rise of the Internet and the exponential increase in data have made manual data summarization and analysis a challenging task. Instagram social network is a prominent social network widely utilized in Iran for information sharing and communication across various age groups. The inherent structure of Instagram, characterized by its text-rich content and graph-like data representation, enables the utilization of text and graph processing techniques for data analysis purposes. The degree distributions of these networks exhibit scale-free characteristics, indicating non-random growth patterns. Recently, word co-occurrence has gained attention from researchers across multiple disciplines due to its simplicity and practicality. Keyword extraction is a crucial task in natural language processing. In this study, we demonstrated that high-precision extraction of keywords from Instagram posts in the Persian language can be achieved using unsupervised word co-occurrence methods without resorting to conventional techniques such as clustering or pre-trained models. After graph visualization and community detection, it was observed that the top topics covered by news agencies are represented by these graphs. This approach is generalizable to new and diverse datasets and can provide acceptable outputs for new data. To the author's knowledge, this method has not been employed in the Persian language before on Instagram social network. The new crawled data has been publicly released on GitHub for exploration by other researchers. By employing this method, it is possible to use other graph-based algorithms, such as community detections. The results help us to identify the key role of different news agencies in information diffusion among the public, identify hidden communities, and discover latent patterns among a massive amount of data. |
| format | Article |
| id | doaj-art-83798c901b024588be069cc7998cf2cd |
| institution | OA Journals |
| issn | 2645-4343 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | University of science and culture |
| record_format | Article |
| series | International Journal of Web Research |
| spelling | doaj-art-83798c901b024588be069cc7998cf2cd2025-08-20T01:57:24ZengUniversity of science and cultureInternational Journal of Web Research2645-43432023-01-0161495810.22133/ijwr.2023.405593.1177Analysis of Persian News Agencies on Instagram, A Words Co-occurrence Graph-based ApproachMohammad Heydari0https://orcid.org/0000-0002-7650-5924Babak Teimourpour1School of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, IranAssistant Professor, School of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, IranThe rise of the Internet and the exponential increase in data have made manual data summarization and analysis a challenging task. Instagram social network is a prominent social network widely utilized in Iran for information sharing and communication across various age groups. The inherent structure of Instagram, characterized by its text-rich content and graph-like data representation, enables the utilization of text and graph processing techniques for data analysis purposes. The degree distributions of these networks exhibit scale-free characteristics, indicating non-random growth patterns. Recently, word co-occurrence has gained attention from researchers across multiple disciplines due to its simplicity and practicality. Keyword extraction is a crucial task in natural language processing. In this study, we demonstrated that high-precision extraction of keywords from Instagram posts in the Persian language can be achieved using unsupervised word co-occurrence methods without resorting to conventional techniques such as clustering or pre-trained models. After graph visualization and community detection, it was observed that the top topics covered by news agencies are represented by these graphs. This approach is generalizable to new and diverse datasets and can provide acceptable outputs for new data. To the author's knowledge, this method has not been employed in the Persian language before on Instagram social network. The new crawled data has been publicly released on GitHub for exploration by other researchers. By employing this method, it is possible to use other graph-based algorithms, such as community detections. The results help us to identify the key role of different news agencies in information diffusion among the public, identify hidden communities, and discover latent patterns among a massive amount of data.https://ijwr.usc.ac.ir/article_186781_de5edc5627e528914c1cff42c47b1693.pdfinstagramnetwork sciencesocial network analysisgraph mining |
| spellingShingle | Mohammad Heydari Babak Teimourpour Analysis of Persian News Agencies on Instagram, A Words Co-occurrence Graph-based Approach International Journal of Web Research network science social network analysis graph mining |
| title | Analysis of Persian News Agencies on Instagram, A Words Co-occurrence Graph-based Approach |
| title_full | Analysis of Persian News Agencies on Instagram, A Words Co-occurrence Graph-based Approach |
| title_fullStr | Analysis of Persian News Agencies on Instagram, A Words Co-occurrence Graph-based Approach |
| title_full_unstemmed | Analysis of Persian News Agencies on Instagram, A Words Co-occurrence Graph-based Approach |
| title_short | Analysis of Persian News Agencies on Instagram, A Words Co-occurrence Graph-based Approach |
| title_sort | analysis of persian news agencies on instagram a words co occurrence graph based approach |
| topic | instagram network science social network analysis graph mining |
| url | https://ijwr.usc.ac.ir/article_186781_de5edc5627e528914c1cff42c47b1693.pdf |
| work_keys_str_mv | AT mohammadheydari analysisofpersiannewsagenciesoninstagramawordscooccurrencegraphbasedapproach AT babakteimourpour analysisofpersiannewsagenciesoninstagramawordscooccurrencegraphbasedapproach |