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Article
Publication date: 1 June 2015

Tadahiko Kumamoto, Hitomi Wada and Tomoya Suzuki

The purpose of this paper is to propose a Web application system for visualizing Twitter users based on temporal changes in the impressions received from the tweets posted by the…

Abstract

Purpose

The purpose of this paper is to propose a Web application system for visualizing Twitter users based on temporal changes in the impressions received from the tweets posted by the users on Twitter.

Design/methodology/approach

The system collects a specified user’s tweets posted during a specified period using Twitter API, rates each tweet based on three distinct impressions using an impression mining system, and then generates pie and line charts to visualize results of the previous processing using Google Chart API.

Findings

Because there are more news articles featuring somber topics than those featuring cheerful topics, the impression mining system, which uses impression lexicons created from a newspaper database, is considered to be more effective for analyzing negative tweets.

Research limitations/implications

The system uses Twitter API to collect tweets from Twitter. This suggests that the system cannot collect tweets of the users who maintain private timelines. According to our questionnaire, about 30 per cent of Twitter users’ timelines are private. This is one of the limitations to using the system.

Originality/value

The system enables people to grasp the personality of Twitter users by visualizing the impressions received from tweets the users normally post on Twitter. The target impressions are limited to those represented by three bipolar scales of impressions: “Happy/Sad”, “Glad/Angry” and “Peaceful/Strained”. The system also enables people to grasp the context in which keywords are used by visualizing the impressions from tweets in which the keywords were found.

Details

International Journal of Pervasive Computing and Communications, vol. 11 no. 2
Type: Research Article
ISSN: 1742-7371

Keywords

Article
Publication date: 30 April 2019

Hiroshi Asaoka, Tomoya Takahashi, Jiafei Chen, Aya Fujiwara, Masataka Watanabe and Fumiyuki Noro

The purpose of this paper is to investigate why children with autism spectrum disorder (ASD) tend to respond to tasks from their own perspective. The authors investigated the…

Abstract

Purpose

The purpose of this paper is to investigate why children with autism spectrum disorder (ASD) tend to respond to tasks from their own perspective. The authors investigated the effects of explicitness of viewpoint on performance of spontaneous level 2 perspective-taking skills in six- to eight-year-old children with ASD.

Design/methodology/approach

The authors conducted visual perspective-taking tasks with explicit and implicit instructions about the viewpoint to be used. Participants operated a toy car on a map while listening to the experimenter’s instructions. In the implicit condition, when the experimenter said “Turn right/left” at each intersection, the participants moved the car accordingly. Subsequently, in the explicit condition, the experimenter said “Look from the driver’s viewpoint and turn right/left” at each intersection.

Findings

In the implicit condition, the authors did not observe a clear developmental change in performance between six- and eight-year-old children in the ASD group. In contrast, performance in the ASD group improved under the explicit condition relative to that under the implicit condition.

Originality/value

The results suggest six- to eight-year-old children with ASD tend not to spontaneously use level 2 perspective-taking skills. Therefore, viewpoints should be explicitly instructed to children with ASD. In addition, it is also important to implement training to encourage spontaneous transitions from self-perspective to other-perspective under the implicit condition.

Details

Advances in Autism, vol. 5 no. 4
Type: Research Article
ISSN: 2056-3868

Keywords

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