A Framework for Mining Thai Public Opinions

Book chapter abstract


ผู้เขียน/บรรณาธิการ


กลุ่มสาขาการวิจัยเชิงกลยุทธ์

ไม่พบข้อมูลที่เกี่ยวข้อง


รายละเอียดสำหรับงานพิมพ์

รายชื่อผู้แต่งDeerosejanadej C., Prom-on S., Achalakul T.

ผู้เผยแพร่Hindawi

ปีที่เผยแพร่ (ค.ศ.)2016

หน้าแรก339

หน้าสุดท้าย355

จำนวนหน้า17

ISBN9780128093467; 9780128053942

นอก0146-9428

eISSN1745-4557

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84988799184&doi=10.1016%2fB978-0-12-805394-2.00014-3&partnerID=40&md5=56c1e0be05393914dca55ac99b6aae82

ภาษาEnglish-Great Britain (EN-GB)


ดูบนเว็บไซต์ของสำนักพิมพ์


บทคัดย่อ

User-generated textual opinions strongly influence humans' beliefs and decisions. Due to the rapid growth of social data, readers cannot capture major opinions on particular topics by reading through all texts. To provide informative supporting evidence for sentiment analysis results, we integrate an opinion summarization framework into a Data and Opinion Mining (DOM) engine, which is an extension of a mobile Big Data analytics engine for mining Thai public opinions (XDOM). This opinion summarization framework is based on a modified genetic sentence clustering and sentence selection. This chapter presents the development of XDOM, which takes in data from multiple well-known social network sources, and then processes them using MapReduce, a keyword-based sentiment analysis technique, a clustering-based text summarization, and an influencer analysis algorithm. The XDOM engine is capable of identifying overall sentiments, representative text summaries, and influential authors of certain topics. The system's sentiment prediction accuracy was evaluated by matching the predicted result with human sentiment and tested in various case studies. The effectiveness of both approaches demonstrates the practical applications of the engine. ฉ 2016 Elsevier Inc. All rights reserved.


คำสำคัญ

MapReduceopinion miningopinion summarizationpublic sentimentsentence clustering


อัพเดทล่าสุด 2023-28-09 ถึง 07:35