How to mine brand Tweets: Procedural guidelines and pretest
| Autor: | Héctor David Menéndez-Benito, Ana María Díaz-Martín, Shintaro Okazaki, Mercedes Rozano |
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| Rok vydání: | 2014 |
| Předmět: | |
| Zdroj: | International Journal of Market Research. 56:467-488 |
| ISSN: | 2515-2173 1470-7853 |
| DOI: | 10.2501/ijmr-2014-008 |
| Popis: | This paper presents a methodological framework for using opinion mining to analyse comments on social networking sites. A series of procedural recommendations is described and compared with the content analysis method. The major steps include brand selection, determination of a classification scheme and categories, human coding, programming of the automated classification algorithm, and evaluation of the classification results. We then present the results of a pretest that examined the content of Tweets about IKEA. After human coding of 100 Tweets, the automated classification was carried out. The Precision measure achieved more than 65% for the first classification (Satisfaction, Dissatisfaction and Exclude) and 64% for the second classification (Sharing, Information, Opinion, Question, Reply and Exclude), demonstrating the efficiency of mining Tweets for emotional patterns. Combining the two classification schemes, the pretest performs a social network analysis to identify interrelationships among the Tweets. In closing, methodological implications and utility for marketing research are discussed. |
| Databáze: | OpenAIRE |
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