In this paper we report research results investigating microblogging as a form of electronic word-of-mouth for sharing consumer opinions concerning brands. We analyzed more than 150,000 microblog postings containing branding comments, sentiments, and opinions. We investigated the overall structure of these microblog postings, the types of expressions, and the movement in positive or negative sentiment. We compared automated methods of classifying sentiment in these microblogs with manual coding. Using a case study approach, we analyzed the range, frequency, timing, and content of tweets in a corporate account. Our research findings show that 19% of microblogs contain mention of a brand. Of the branding microblogs, nearly 20% contained some expression of brand sentiments. Of these, more than 50% were positive and 33% were critical of the company or product. Our comparison of automated and manual coding showed no significant differences between the two approaches. In analyzing microblogs for structure and composition, the linguistic structure of tweets approximate the linguistic patterns of natural language expressions. We find that microblogging is an online tool for customer word of mouth communications and discuss the implications for corporations using microblogging as part of their overall marketing strategy.

major Internet search service. We provide data on: (i) sessions -changes in queries during a session, number of pages viewed, and use of relevance feedback, (ii) queries -the number of search terms, and the use of logic and modifiers, and (iii) terms -their rank/frequency distribution and the most highly used search terms. We then shift the focus of analysis from the query to the user to gain insight to the characteristics of the Web user. With these characteristics as a basis, we then conducted a failure analysis, identifying trends among user mistakes. We conclude with a summary of findings and a discussion of the implications of these findings.

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We analyzed transaction logs of a set of 51,473 queries posed by 18,113 users of Excite, a major Internet search service. We provide data on: (i) queries --- the number of search terms, and the use of logic and modifiers, (ii) sessions --- changes in queries during a session, number of pages viewed, and use of relevance feedback, and (iii) terms --- their rank/frequency distribution and the most highly used search terms. Common mistakes are also observed. Implications are discussed.