Details

Autor(en) / Beteiligte

• Hashimoto, Takako
• Shirota, Yukari
• Kikuchi, Shinji
• Bhalla, Subhash
• Sachdeva, Shelly

Titel

Semantics Extraction from Social Computing: A Framework of Reputation Analysis on Buzz Marketing Sites

Ist Teil von

• Databases in Networked Information Systems, p.244-255

Ort / Verlag

Berlin, Heidelberg: Springer Berlin Heidelberg

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Social computing services, which enable people to easily communicate and effectively share the information through the Web, have rapidly spread recently. In the marketing research domain, buzz marketing sites as social computing services have become important in recognizing the reputation of products hold with users. This paper proposes a reputation analysis framework for the buzz marketing sites. Our framework consists of four steps: the first is to extract the topics of the product using natural language processing. The input data comprises consumer messages on buzz marketing sites. Next, important topics on the products are extracted. The third step is to detect emerging consumer needs by identifying new burst topics. Finally, the results are visualized. Based on our framework, product characteristics and emerging consumer needs are extracted and reputations are visualized.