Papers - OKOSHI Tadashi

Investigating the occurrence of selfie-based emotional contagion over social network.

Wataru Sasaki, Yuuki Nishiyama, Tadashi Okoshi, Jin Nakazawa

Soc. Netw. Anal. Min. 11 ( 1 ) 8 - 8 2021

Research paper (scientific journal), Joint Work

• Access to Document (DOI)

NationalMood: Large-scale Estimation of People's Mood from Web Search Query and Mobile Sensor Data

Tadashi Okoshi

CoRR abs/2011.00665 2020.11

Research paper (scientific journal), Single Work

　View Summary

The ability to estimate current affective statuses of web users has considerable potential towards the realization of user-centric opportune services. However, determining the type of data to be used for such estimation as well as collecting the ground truth of such affective statuses are difficult in the real world situation. We propose a novel way of such estimation based on a combinational use of user's web search queries and mobile sensor data. Our large-scale data analysis with about 11,000,000 users and 100 recent advertisement log revealed (1) the existence of certain class of advertisement to which mood-status-based delivery would be significantly effective, (2) that our "National Mood Score" shows the ups and downs of people's moods in COVID-19 pandemic that inversely correlated to the number of patients, as well as the weekly mood rhythm of people.

A mobility-aware pub/sub architecture for short-lived data in smart cities: poster abstract.

Takafumi Kawasaki, Tadashi Okoshi, Jin Nakazawa

  645 - 646 2020

Research paper (international conference proceedings), Joint Work

• Access to Document (DOI)

Element Recognition of Step Sequences in Figure Skating Using Deep Learning Model

岩田あきほ, 川島寛乃, 大越匡, 中澤仁

情報処理学会研究報告(Web) 2020 ( CDS-28 )  2020

Joint Work

Mobile Computing-based Emotional Eating Detection

栄元優作, 佐々木航, 西山勇毅, 大越匡, 中澤仁

情報処理学会研究報告(Web) 2020 ( MBL-94 )  2020

Joint Work

フットサル動画分析のためのデータ収集システム

大村昇平, 谷村朋樹, 大越匡, 中澤仁

情報処理学会研究報告(Web) 2020 ( CDS-28 )  2020

Joint Work

Making Cities Smarter with Fine-grained Environmental Information

大越匡, 中澤仁

水環境学会誌 43(A) ( 11 )  2020

Joint Work,  ISSN  0916-8958

WellComp 2020: third international workshop on computing for well-being.

Tadashi Okoshi, Jin Nakazawa, JeongGil Ko, Fahim Kawsar, Susanna Pirttikangas

  671 - 674 2020

Research paper (international conference proceedings), Joint Work

• Access to Document (DOI)

Using iOS for inconspicuous data collection: a real-world assessment.

Yuuki Nishiyama, Denzil Ferreira, Wataru Sasaki, Tadashi Okoshi, Jin Nakazawa, Anind K. Dey, Kaoru Sezaki

  261 - 266 2020

Research paper (international conference proceedings), Joint Work

• Access to Document (DOI)

UbiTtention 2020: 5th International Workshop on Smart & Ambient Notification and Attention Management.

Niels van Berkel, Anja Exler, Martin Gjoreski, Tine Kolenik, Tadashi Okoshi, Veljko Pejovic, Aku Visuri, Alexandra Voit

  431 - 435 2020

Research paper (international conference proceedings), Joint Work

• Access to Document (DOI)

SmileCityReport: Emotion-aware Participatory Sensing for Smart Cities with Double-sided Photo Shooting.

Wataru Sasaki, Yusaku Eigen, Arturo Medela, Antonis Litke, Vanessa Clemente Núñez, Tadashi Okoshi, Jin Nakazawa

  1 - 6 2020

Research paper (international conference proceedings), Joint Work

• Access to Document (DOI)

Keynote: Digital-Wellbeing powered by IT/AI Technologies.

Tadashi Okoshi

  1 - 1 2020

Research paper (international conference proceedings), Single Work

• Access to Document (DOI)

IOS Crowd-Sensing Won't Hurt a Bit!: AWARE Framework and Sustainable Study Guideline for iOS Platform.

Yuuki Nishiyama, Denzil Ferreira, Yusaku Eigen, Wataru Sasaki, Tadashi Okoshi, Jin Nakazawa, Anind K. Dey, Kaoru Sezaki

  223 - 243 2020

Research paper (international conference proceedings), Joint Work

• Access to Document (DOI)

Measuring a Performance of Mobile Sensing Framework for iOS in an In-the-Wild Study

西山勇毅, 佐々木航, 栄元優作, 本木悠介, 大越匡, 中澤仁, 瀬崎薫

電子情報通信学会技術研究報告 119 ( 477(LOIS2019 56-84)(Web) )  2020

Joint Work,  ISSN  0913-5685

Estimating symptoms caused by CIPN using mobile and wearable devices.

Wataru Sasaki, Ryo Ozawa, Tadashi Okoshi, Jin Nakazawa, Kaori Yagasaki, Hiroko Komatsu

  696 - 699 2020

Research paper (international conference proceedings), Joint Work

• Access to Document (DOI)

ER-Chat: Response Text Generation for Dialogue System with Emotional Regulation

片山晋, 米澤拓郎, 大越匡, 中澤仁, 河口信夫, 河口信夫

情報処理学会研究報告(Web) 2020 ( HCI-190 )  2020

Joint Work

Behavification: bypassing human's attentional and cognitive systems for automated behavior change.

Tadashi Okoshi, Wataru Sasaki, Jin Nakazawa

  692 - 695 2020

Research paper (international conference proceedings), Joint Work

• Access to Document (DOI)

Understanding Smartphone Notifications’ User Interactions and Content Importance

A Visuri, N van Berkel, T Okoshi, J Goncalves, V Kostakos

International Journal of Human-Computer Studies (International Journal of Human Computer Studies)  128   72 - 85 2019.08

ISSN  10715819

　View Summary

© 2019 Elsevier Ltd We present the results of our experiment aimed to comprehensively understand the combination of 1) how smartphone users interact with their notifications, 2) what notification content is considered important, 3) the complex relationship between the interaction choices and content importance, and lastly 4) establish an intelligent method to predict user's preference to seeing an incoming notification. We use a dataset of notifications received by 40 anonymous users in-the-wild, which consists of 1) qualitative user-labelled information about their preferences on notification's contents, 2) notification source, and 3) the context in which the notification was received. We assess the effectiveness of personalised prediction models generated using a combination of self-reported content importance and contextual information. We uncover four distinct user types, based on the number of daily notifications and interaction choices. We showcase how usage traits of these groups highlight the requirement for notification filtering approaches, e.g., when specific users habitually neglect to manually filter out unimportant notifications. Our machine learning-based predictor, based on both contextual sensing and notification contents can predict the user's preference for successfully acknowledging an incoming notification with 91.1% mean accuracy, crucial for time-critical user engagement and interventions.

• Access to Document (DOI)

AffectiveNemo: Promoting Owner-Fish Interaction by Displaying Observed Fish Emotion with Speech Bubble.

Naohiro Isokawa, Jin Nakazawa, Tadashi Okoshi

  18 - 5 2019

Research paper (international conference proceedings), Joint Work

• Access to Document (DOI)

人の限定合理性を超越した行動変容支援に向けた情報プラットフォームの設計

大越 匡, 西山 勇毅, 佐々木 航, 栄元 優作, 中澤 仁

情報処理学会研究報告. UBI, [ユビキタスコンピューティングシステム] 2019 ( UBI-64 ) 1 2019

Joint Work, Accepted