Tetsuro Takahashi

Rumor detection on twitter

Twitter is useful in a situation of disaster for communication, announcement, request for rescue and so on. On the other hand, it causes a negative by-product, spreading rumors. This paper describe how rumors have spread after a disaster of earthquake, and discuss how can we deal with them. We first investigated actual instances of rumor after the disaster. And then we attempted to disclose characteristics of those rumors. Based on the investigation we developed a system which detects candidates of rumor from twitter and then evaluated it. The result of experiment shows the proposed algorithm can find rumors with acceptable accuracy.

Can twitter be an alternative of real-world sensors?

Twitter is the most famous on-line microblogging service now. People can post (tweet) what they are doing in 140 characters. Since Twitter posts (tweets) reflect what people are looking, hearing, feeling and so on, we can obtain information about Real-world phenomena through the large amount of tweets. In other words, Twitter can be regarded as a sensor of Real-world phenomena including natural phenomena such as hay fever. This motivated us to investigate whether can Twitter be an alternative of Real-world Sensor. In this paper, we first describe about our system which collects and analyzes tweets in order to generates a hay fever map just like as a weather report map. There are some difficulties such as location estimation and normalization of number of tweets. Using the output of the system, we discuss the comparison with actual pollen data gathered by real sensors. The result shows that Twitter can reflect natural phenomena in some particular areas.

RSS feed generation from legacy HTML pages

Although RSS demonstrates a promising solution to track and personalize the flow of new Web information, many of the current Web sites are not yet enabled with RSS feeds. The availability of convenient approaches to “RSSify” existing suitable Web contents has become a stringent necessity. This paper presents a system that translates semi-structured HTML pages to structured RSS feeds, which proposes different approaches based on various features of HTML pages. For the information items with release time, the system provides an automatic approach based on time pattern discovery. Another automatic approach based on repeated tag pattern mining is applied to convert the regular pages without the time pattern. A semi-automatic approach based on labelling is available to process the irregular pages or specific sections in Web pages according to the user’s requirements. Experimental results and practical applications prove that our system is efficient and effective in facilitating the RSS feed generation.