Twitter messages are real-time, spontaneous reports of what the users are feeling, thinking, and doing. The frequency of posting "Tweets" oscillates periodically in one-day and seven-day cycles. These periodic patterns may be related to the individual users' baseline affective state. In order to investigate individual periodic behavior in social media, we performed a Fourier series expansion and PCA on intra-week Tweet-frequency changes of 11,570 individuals. Moreover, the relationships between the users' baseline mood and the principal component scores were investigated. High frequency in daytime tweets on weekdays was found to be linked to a low positive affective state. The larger number of posting tweets was related to the negative affective state.

We investigate leadership behaviors in online communication to develop reliable relationships with others, by integrating questionnaire survey with influential human networks extracted by the IDM (influence diffusion model). Questionnaire survey is applied to 97 staffs working in an NPO (nonprofit organization) in Japan to understand the reliability toward leaders from the other staffs. Influential human networks are extracted from the archives of E-mail used in the NPO to understand influential relationships between leaders and the other staffs over E-mail. Simply put what we discovered, a leader should catch staffs' messages and reply to them as well as throw new messages to construct reliable relationships. Otherwise, a leader becomes self-righteous, and lose reliabilities from the other staffs.

It is difficult to carry out quantitative measurements of the persuasive power of business communications (i.e., persuasive skills) and such communications are likely to involve difficult to understand, unseen and unknown knowledge. However, using unstructured recorded communication data based on conversations with business customers, we have been developing explicit knowledge concerning skills necessary for effective communications in the form of an expression framework. The objective of this research is to generate a framework and a process for explicit management knowledge concerning understandable communication skills as opposed to the tacit, hard to understand the negotiating skills related to overdue payment collection personnel and to verify the actual usefulness of this knowledge using the accumulated data in a company. Using this process we have developed, it is possible to discover the special characteristics of the communication content of high success overdue payment collection personnel.

We determined the results of the questionnaire for 97 staff members working in dot-jp, a non-profit organization in Japan, to understand the degrees of satisfaction of staff members with leaders. We then extracted human influence networks from the archives of e-mail used at dot-jp to understand relationships between leaders and other staff members. By integrating these two approaches, we revealed ideal leadership behavior. We discovered that leaders should receive messages from staff members as well as send messages to construct reliable relationships. Otherwise, leaders become smug and lose trusts from other staff members

Textual communication in message boards is analyzed for classifying Web communities. We present a communication-content based generalization of an existing business-oriented classification of Web communities, using KeyGraph, a method for visualizing the co-occurrence relations between words and word clusters in text. Here, the text in a message board is analyzed with KeyGraph, and the structure obtained is shown to reflect the essence of the content-flow. The relation of this content-flow with participants' interests is then formalized. Three structure-features of relations between participants and words, determining the type of the community, are shown to be computed and visualized: (1) centralization (2) context coherence and (3) creative decisions. This helps in surveying the essence of a community, e.g. whether the community creates useful knowledge, how easy it is to join the community, and whether/why the community is good for making commercial advertisement.

The phenomenon that a 'little' topic can make a big difference is called 'The Tipping Point'. As a strategy for marketing this phenomenon could be a great economic opportunity. For instance, at is a good strategy to promote items associated with a certain fashion. The Tipping Point refers to a situation where the topic matches potential needs of customers. We analyze the mechanism of The Tipping Point in the context of the WWW, and present an algorithm called 'Expected Activation' for discovering promising new topics on the WWW.