Method for measuring Twitter content influence

Twitter is a microblogging website with specific characteristics not found in other social network services. This platform contains a good deal of valuable content, and users can access this content using Twitter search. However, Twitter search returns only time-descending ordered content including keywords. Thus, we propose a linear-time method of measuring the influence of Twitter content considering not only time, but also characteristics of each Twitter account. In analyzing these characteristics, we have found that the number of retweets can measure shareability, while the number of followers held by the content author can measure spreadability. We perform experiments using real Twitter data for proving the effectiveness of the proposed method. We demonstrate that this proposed method is effective at finding up-to-date content. Further, in comparing our method with analysis via PageRank, we demonstrate that our method is more effective at accurately measuring influence.