| （英） |
With the spread of coronavirus infection, it has become difficult to collect information face-to-face with students who are looking for a job. As a result, students are forced to engage in non-face-to-face activities, and the use of SNS such as Twitter, Facebook, and Instagram is rapidly increasing as a means of collecting information. At the same time, the need for IT literacy for collecting information on SNS is also increasing. Therefore, in this paper, we propose a method to classify useful information and non-useful information for students in job hunting on Twitter, which is suitable for non-face-to-face and sharing of important information. The proposed method uses correlation and regression analysis to determine the causal relationship between the usefulness of the account and the traces that occur in the operation of Twitter. |