Topic Extraction Analysis for Sidoardjo Mudflow Disaster Impacts

In this paper, we present our work on analyzing the impact of the Mudflow Disaster in Sidoardjo, Indonesia, based on text mining technologies. We conducted a topic extraction using the Latent Dirichlet Allocation model. To handle the difficult expressions and grasp the points, we use various techniques such as bigram segmentation for documents related to the Mudflow in English. The TreeTagger is the morphological analysis tool used. The extracted topics clearly showed the impact of the Sidoardjo Mudflow. The most widely discussed topic found was the resettlement conditions and the compensation for the victim corresponding to the presidential regulation. We also found other frequently mentioned topics, such as the payment of resettlement, water pollution, and the verification process for the households

A study of Beethoven’s Symphony No.5 c-minor Op.67 (Fate)\nused as standard teaching material in a junior high school music class

As part of junior high school music education in Japan, both standard singing teaching materials and standard listening teaching materials have been assigned according to successive Department of Education directives (1958, 1969, 1977, and 1989). However, these were not specified for the 1998 directive on teaching guidelines. For the 2008 guidelines, seven compositions by Japanese composers remain, but directives regarding standard listening teaching materials were not included. Among the previous directives (1977, 1989) Beethoven’s Symphony No.5 c-minor Op.67 (named ‘Fate’ in Japan) was assigned as part of the curriculum for both second grade students. This paper will attempt to examine the adequacy of descriptions of this Beethoven’s symphony in three textbooks assigned as part of music education in Japan

Visual analytics of location-based social networks for decision support

Recent advances in technology have enabled people to add location information to social networks called Location-Based Social Networks (LBSNs) where people share their communication and whereabouts not only in their daily lives, but also during abnormal situations, such as crisis events. However, since the volume of the data exceeds the boundaries of human analytical capabilities, it is almost impossible to perform a straightforward qualitative analysis of the data. The emerging field of visual analytics has been introduced to tackle such challenges by integrating the approaches from statistical data analysis and human computer interaction into highly interactive visual environments. Based on the idea of visual analytics, this research contributes the techniques of knowledge discovery in social media data for providing comprehensive situational awareness. We extract valuable hidden information from the huge volume of unstructured social media data and model the extracted information for visualizing meaningful information along with user-centered interactive interfaces. We develop visual analytics techniques and systems for spatial decision support through coupling modeling of spatiotemporal social media data, with scalable and interactive visual environments. These systems allow analysts to detect and examine abnormal events within social media data by integrating automated analytical techniques and visual methods. We provide comprehensive analysis of public behavior response in disaster events through exploring and examining the spatial and temporal distribution of LBSNs. We also propose a trajectory-based visual analytics of LBSNs for anomalous human movement analysis during crises by incorporating a novel classification technique. Finally, we introduce a visual analytics approach for forecasting the overall flow of human crowds

Uncovering the myth of learning to read Chinese characters: phonetic, semantic, and orthographic strategies used by Chinese as foreign language learners

Oral Session - 6A: Lexical modeling: no. 6A.3Chinese is considered to be one of the most challenging orthographies to be learned by non-native speakers, in particular, the character. Chinese character is the basic reading unit that converges sound, form and meaning. The predominant type of Chinese character is semantic-phonetic compound that is composed of phonetic and semantic radicals, giving the clues of the sound and meaning, respectively. Over the last two decades, psycholinguistic research has made significant progress in specifying the roles of phonetic and semantic radicals in character processing among native Chinese speakers …postprin

(Dis)connections between specific language impairment and dyslexia in Chinese

Poster Session: no. 26P.40Specific language impairment (SLI) and dyslexia describe language-learning impairments that occur in the absence of a sensory, cognitive, or psychosocial impairment. SLI is primarily defined by an impairment in oral language, and dyslexia by a deficit in the reading of written words. SLI and dyslexia co-occur in school-age children learning English, with rates ranging from 17% to 75%. For children learning Chinese, SLI and dyslexia also co-occur. Wong et al. (2010) first reported on the presence of dyslexia in a clinical sample of 6- to 11-year-old school-age children with SLI. The study compared the reading-related cognitive skills of children with SLI and dyslexia (SLI-D) with 2 groups of children …postprin