{"id":1441,"date":"2024-11-27T10:56:19","date_gmt":"2024-11-27T10:56:19","guid":{"rendered":"https:\/\/wp.lancs.ac.uk\/factor\/?p=1441"},"modified":"2025-01-04T14:09:27","modified_gmt":"2025-01-04T14:09:27","slug":"hettiarachchi-temporal-word-dynamics-for-online-event-detection-in-social-media-streams","status":"publish","type":"post","link":"http:\/\/wp.lancs.ac.uk\/factor\/2024\/11\/27\/hettiarachchi-temporal-word-dynamics-for-online-event-detection-in-social-media-streams\/","title":{"rendered":"Hettiarachchi – Temporal word dynamics for online event detection in social media streams"},"content":{"rendered":"

FACTOR is pleased to announce our next talk in the 2024-2025 academic year by Dr Hansi Hettiarachchi<\/a> (Computing<\/a>,\u00a0SPS<\/a>, Lancaster University):<\/p>\n

TITLE<\/strong><\/p>\n

Temporal word dynamics for online event detection in social media streams<\/p>\n

ABSTRACT<\/strong><\/p>\n

In today’s digital era, social media have become primary platforms for disseminating newsworthy content, with most internet users relying on them for regular updates. Thus, understanding and detecting important events from social media data streams is vital for various applications ranging from crisis management to market analysis. However, the vast volume and unstructured nature of this data, generated by a diverse range of users, make manual detection methods highly labour-intensive. As a result, automated intelligent mechanisms have become essential for efficiently handling event detection tasks. However, most available social media event detection approaches primarily rely on data statistics, ignoring semantics, making them vulnerable to critical information loss. Following this gap, this presentation will explore how temporal word dynamics can be involved in achieving effective event detection from social media data.<\/p>\n

TIME & PLACE<\/strong><\/p>\n

W09, 1500-1550, Thu 05th Dec 2024, Bowland North SR02<\/a>. (Please note that this talk will not<\/strong> be streamed or recorded.)<\/p>\n

Find information on how to get to campus here<\/a>, and how to navigate campus buildings here<\/a>.<\/p>\n

REGISTRATION<\/strong><\/p>\n

For accessibility, fire, and safety compliance, please register before attending<\/strong><\/a>.<\/p><\/blockquote>\n","protected":false},"excerpt":{"rendered":"FACTOR is pleased to announce our next talk in the 2024-2025 academic year by Dr Hansi Hettiarachchi (Computing,\u00a0SPS, Lancaster University): TITLE Temporal word dynamics for online event detection in social media streams ABSTRACT In today’s digital era, social media have become primary platforms for disseminating newsworthy content, with most internet users relying on them for […]","protected":false},"author":77,"featured_media":1454,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"episode_type":"audio","audio_file":"","podmotor_file_id":"","podmotor_episode_id":"","cover_image":"","cover_image_id":"","duration":"","filesize":"","filesize_raw":"","date_recorded":"","explicit":"","block":"","itunes_episode_number":"","itunes_title":"","itunes_season_number":"","itunes_episode_type":"","jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1],"tags":[],"series":[],"class_list":["post-1441","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"episode_featured_image":"http:\/\/wp.lancs.ac.uk\/factor\/files\/2024\/11\/OIG3.jpeg","episode_player_image":"https:\/\/i0.wp.com\/wp.lancs.ac.uk\/factor\/files\/2018\/11\/cover_2000.png?fit=2000%2C2000","download_link":"","player_link":"","audio_player":false,"episode_data":{"playerMode":"dark","subscribeUrls":[],"rssFeedUrl":"http:\/\/wp.lancs.ac.uk\/factor\/feed\/podcast\/the-forge","embedCode":"

Hettiarachchi – Temporal word dynamics for online event detection in social media streams<\/a><\/blockquote>