Personal learning networks and personal learning environmentsTumelo Matlou
This document discusses personal learning environments (PLEs) and connectivism as a learning theory for the digital age. It explains that PLEs allow learners to take control of and manage their own learning through goals, content, communication, and achieving learning outcomes. PLEs involve self-organized learning across different contexts through personal web tools, networks, and experiences beyond formal education. The transition from PLEs to personal learning networks (PLNs) further supports lifelong, self-organized learning.
This document outlines Heidi Garrett-Peltier's presentation on the work of the Political Economy Research Institute (PERI). PERI conducts policy-oriented economic research to improve human and environmental well-being. Examples of recent projects include a study on controlling climate change through green growth and job creation in the US. PERI aims to produce high-quality research and write for non-academic audiences. Effectiveness is harder to measure than traditional academic work but can be seen through policy impacts, media references, social media engagement, and other feedback from target audiences.
Personal learning networks and personal learning environmentsTumelo Matlou
This document discusses personal learning environments (PLEs) and connectivism as a learning theory for the digital age. It explains that PLEs allow learners to take control of and manage their own learning through goals, content, communication, and achieving learning outcomes. PLEs involve self-organized learning across different contexts through personal web tools, networks, and experiences beyond formal education. The transition from PLEs to personal learning networks (PLNs) further supports lifelong, self-organized learning.
This document outlines Heidi Garrett-Peltier's presentation on the work of the Political Economy Research Institute (PERI). PERI conducts policy-oriented economic research to improve human and environmental well-being. Examples of recent projects include a study on controlling climate change through green growth and job creation in the US. PERI aims to produce high-quality research and write for non-academic audiences. Effectiveness is harder to measure than traditional academic work but can be seen through policy impacts, media references, social media engagement, and other feedback from target audiences.
La pandemia de COVID-19 ha tenido un impacto significativo en la economía mundial. Muchos países experimentaron fuertes caídas en el PIB y aumentos en el desempleo debido a los cierres generalizados y las restricciones a los viajes. Aunque las vacunas han permitido la reapertura de muchas economías, los efectos a largo plazo de la pandemia en sectores como el turismo y los viajes aún no están claros. Se espera que la recuperación económica mundial sea desigual y dependa de factores como el control
Detecting Misleading Headlines in Online News: Hands-on Experiences on Attent...Kunwoo Park
This slide is used for the tutorial in Deep Learning Summer School, held in IBS, Daejeon. Based on the recent effort on detecting misleading headlines through deep neural networks (Yoon et al., AAAI 2019), it explains how RNN and Attention mechanism works for text. Moreover, implementations based on TensorFlow 1.x are introduced.
Positivity Bias in Customer Satisfaction RatingsKunwoo Park
This slide is for my presentation at The Web Conference 2018 (also known as WWW). You can check the paper at the following link: https://dl.acm.org/authorize.cfm?key=N655133
Persistent Sharing of Fitness App Status on TwitterKunwoo Park
2016년 7월 25일 Naver labs에서 발표한 자료입니다. CSCW '16에서 발표된 아래 논문을 한글로 소개하였습니다.
Title: Persistent Sharing of Fitness App Status on Twitter
Author: Kunwoo Park, Ingmar Weber, Meeyoung Cha, Chul Lee
소셜 데이터를 이용한 연구소개 - 피트니스 앱의 지속 사용에 관한 연구Kunwoo Park
2015년 12월 18일 한빛미디어에서 개최된 생활 데이터 모임에서 발표한 내용입니다. 소셜 데이터를 이용한 연구 사례로 피트니스 앱의 지속 사용에 관한 연구를 공유하였습니다. 소개된 논문은 다음 링크에서 확인 가능합니다: http://kunwpark.kr/wp-content/uploads/2015/12/cscw16_park.pdf
MS thesis defense - Gender swapping and its effects in MMORPGsKunwoo Park
- The document discusses a study on the phenomenon of gender swapping in MMORPG games and its effects. It analyzes player demographic data from the Fairyland Online game.
- Females are found to participate in gender swapping more than males. Older and more experienced players also swap genders more. Gender swapping is found to affect in-game behaviors and social networks.
- Players' levels increase faster when their avatar gender matches their real gender, following real-world gender roles. Females profit more from trades, also following online gender roles. Social networks are affected by both real and virtual gender.
[DISC2013] Mood and Weather: Feeling the Heat?Kunwoo Park
The document discusses a study that analyzed the relationship between mood expressed on Twitter and weather conditions using a dataset of 38.1 million tweets from the United States in April 2009 along with corresponding weather data. The researchers found a weak positive correlation between temperature and positive sentiment across states on average, but also found some states showed negative correlations. The study concluded that how weather affects mood varies significantly by region due to cultural and economic factors.
[CS570] Machine Learning Team Project (I know what items really are)Kunwoo Park
This document summarizes a team's approach to predicting which items users might be interested in using a recommendation system. It describes extracting features from user and item metadata to train an SVM model, but this was too computationally expensive. Instead, the team used logistic regression with stochastic gradient descent. They tested features like age, gender and network similarities. Their combined model outperformed random prediction baselines on the KDD Cup 2012 Track 1 dataset.
Social Network Analysis:Methods and Applications Chapter 9Kunwoo Park
This document discusses structural equivalence and positional analysis in networks. It defines structural equivalence as two actors having identical ties to and from all other actors. It describes methods for measuring approximate structural equivalence using metrics like Euclidean distance and correlation. It also outlines techniques for partitioning actors into positions based on their structural equivalence, including CONCOR and hierarchical clustering algorithms. The document emphasizes that positional analysis aims to simplify network data by grouping similarly positioned actors.
Social Network Analysis : Methods and Applications Chapter 6 and 7Kunwoo Park
1) The chapter discusses methods for identifying cohesive subgroups within networks, including cliques, n-clans, and lambda sets.
2) Cohesive subgroups are defined as subsets of nodes that are relatively more strongly connected to each other than to nodes outside the subgroup.
3) Different methods take into account factors like reachability between nodes, nodal degree, and comparing the frequency of ties within versus outside the subgroup.
La pandemia de COVID-19 ha tenido un impacto significativo en la economía mundial. Muchos países experimentaron fuertes caídas en el PIB y aumentos en el desempleo debido a los cierres generalizados y las restricciones a los viajes. Aunque las vacunas han permitido la reapertura de muchas economías, los efectos a largo plazo de la pandemia en sectores como el turismo y los viajes aún no están claros. Se espera que la recuperación económica mundial sea desigual y dependa de factores como el control
Detecting Misleading Headlines in Online News: Hands-on Experiences on Attent...Kunwoo Park
This slide is used for the tutorial in Deep Learning Summer School, held in IBS, Daejeon. Based on the recent effort on detecting misleading headlines through deep neural networks (Yoon et al., AAAI 2019), it explains how RNN and Attention mechanism works for text. Moreover, implementations based on TensorFlow 1.x are introduced.
Positivity Bias in Customer Satisfaction RatingsKunwoo Park
This slide is for my presentation at The Web Conference 2018 (also known as WWW). You can check the paper at the following link: https://dl.acm.org/authorize.cfm?key=N655133
Persistent Sharing of Fitness App Status on TwitterKunwoo Park
2016년 7월 25일 Naver labs에서 발표한 자료입니다. CSCW '16에서 발표된 아래 논문을 한글로 소개하였습니다.
Title: Persistent Sharing of Fitness App Status on Twitter
Author: Kunwoo Park, Ingmar Weber, Meeyoung Cha, Chul Lee
소셜 데이터를 이용한 연구소개 - 피트니스 앱의 지속 사용에 관한 연구Kunwoo Park
2015년 12월 18일 한빛미디어에서 개최된 생활 데이터 모임에서 발표한 내용입니다. 소셜 데이터를 이용한 연구 사례로 피트니스 앱의 지속 사용에 관한 연구를 공유하였습니다. 소개된 논문은 다음 링크에서 확인 가능합니다: http://kunwpark.kr/wp-content/uploads/2015/12/cscw16_park.pdf
MS thesis defense - Gender swapping and its effects in MMORPGsKunwoo Park
- The document discusses a study on the phenomenon of gender swapping in MMORPG games and its effects. It analyzes player demographic data from the Fairyland Online game.
- Females are found to participate in gender swapping more than males. Older and more experienced players also swap genders more. Gender swapping is found to affect in-game behaviors and social networks.
- Players' levels increase faster when their avatar gender matches their real gender, following real-world gender roles. Females profit more from trades, also following online gender roles. Social networks are affected by both real and virtual gender.
[DISC2013] Mood and Weather: Feeling the Heat?Kunwoo Park
The document discusses a study that analyzed the relationship between mood expressed on Twitter and weather conditions using a dataset of 38.1 million tweets from the United States in April 2009 along with corresponding weather data. The researchers found a weak positive correlation between temperature and positive sentiment across states on average, but also found some states showed negative correlations. The study concluded that how weather affects mood varies significantly by region due to cultural and economic factors.
[CS570] Machine Learning Team Project (I know what items really are)Kunwoo Park
This document summarizes a team's approach to predicting which items users might be interested in using a recommendation system. It describes extracting features from user and item metadata to train an SVM model, but this was too computationally expensive. Instead, the team used logistic regression with stochastic gradient descent. They tested features like age, gender and network similarities. Their combined model outperformed random prediction baselines on the KDD Cup 2012 Track 1 dataset.
Social Network Analysis:Methods and Applications Chapter 9Kunwoo Park
This document discusses structural equivalence and positional analysis in networks. It defines structural equivalence as two actors having identical ties to and from all other actors. It describes methods for measuring approximate structural equivalence using metrics like Euclidean distance and correlation. It also outlines techniques for partitioning actors into positions based on their structural equivalence, including CONCOR and hierarchical clustering algorithms. The document emphasizes that positional analysis aims to simplify network data by grouping similarly positioned actors.
Social Network Analysis : Methods and Applications Chapter 6 and 7Kunwoo Park
1) The chapter discusses methods for identifying cohesive subgroups within networks, including cliques, n-clans, and lambda sets.
2) Cohesive subgroups are defined as subsets of nodes that are relatively more strongly connected to each other than to nodes outside the subgroup.
3) Different methods take into account factors like reachability between nodes, nodal degree, and comparing the frequency of ties within versus outside the subgroup.
9. Dataset
• 날씨 데이터
•
•
•
•
•
2009, 4월
http://www.wunderground.com
Web crawling
미국의 각 weather station의 날씨 정보들
각 state에 해당하는 weather station들의
날씨 정보 mapping
source: http://www.wunderground.com
2013-10-29
GCT606 Digital Performance
9
12. Approach
• 감성 분석
• LIWC (Linguistic Inquiry and Word Count)
• 긍/부정 감정 제공
• 지역별, 날짜별 평균값 분석
2013-10-29
GCT606 Digital Performance
12
13. Approach
• 상관관계 분석
• 피어슨 상관계수 이용 (Pearson’s r )
• -1 < r < 1
• r 값이 0에 가까우면 둘 간에 관계가 없고, 1에 가까울수록 양의 상관관계가, -1에 가
까울수록 음의 상관관계가 있다.
• 날씨의 변화와 감정의 변화는 어떤 관계가 있는가?
• 예) 온도가 올라갈때 긍정 감정이 같이 올라가는 경향이 있다. r > 0.4
2013-10-29
GCT606 Digital Performance
13
15. Result
• 월 평균 기온 <-> 월평균 긍정 감정
-> 평균 기온이 높은 곳에 살 수록, 긍정적인 경향이 있다.
(r =0.3752)
2013-10-29
GCT606 Digital Performance
15
16. Result
• 일 평균 기온 <-> 일평균 긍정 감정 (주별로)
=> (각각의 여러 주 별로) 일 평균 기온이 높을 수록 긍정 감정도 높은 경향
이 있다. 하지만 그 반대의 경향을 보이는 주도 있다.
2013-10-29
GCT606 Digital Performance
16
17. Result
• 일 평균 습도 <-> 일평균 부정 감정 (주별로)
=> (각각의 여러 주 별로) 일 평균 습도가 높을 수록 부정 감정도 높은 경향
이 있다. 하지만 그 반대의 경향을 보이는 주도 있다.
2013-10-29
GCT606 Digital Performance
17
18. Result
• 일 평균 기압 <-> 일평균 긍정 감정 (주별로)
=> (각각의 여러 주 별로) 일 평균 기압이 높을 수록 긍정 감정도 높은 경향
이 있다. 하지만 그 반대의 경향을 보이는 주도 있다.
2013-10-29
GCT606 Digital Performance
18