1. Section 4: see other Slide Show
Christoph F. Eick
UH-DAIS
Section 4: see other Slide Show
Tweet Emotion Mapping:
Understanding US Emotions in Time and Space
Related to: &
Inspired by:
Great Dismal Swamp, Virginia
Data Analysis and Intelligent Systems Lab

2. Investigated Research Topics
Spatio-Temporal Data Analysis Frameworks that Operate on Continuous Functions, such as Density Functions and Interpolation Functions.
Spatial and Spatio-temporal Clustering and Hotspot Discovery Algorithms
Emotion and Emotion Change Mapping
Design of Animations that Summarize the Change of Emotions for a Region of Interest over a Period of Time
St^2: Tools for Spatio-temporal Storytelling
Also: Create a Website that makes our emotion analysis, animation and data storytelling services available to the public.
Not so much: We mostly rely on tools, designed by other, for the assessment of emotions expressed in text document; e.g. tweets; that is, this subject is not the main focus of our research.

3. Project Goals
Given a set of tweets with the location (longitude and latitude), time they were posted and their emotional assessment in [-1,+1] (+1:=very positive emotions, 0:=no emotions, -1: very negative emotions)
Research Goals:
Identify spatial regions of highly positive emotions (e.g. average emotional assessment >0.4) and regions of highly negative emotions (e.g. average emotion assessment < -0.4) for an observation period; e.g. a year.
Identify spatial regions of high discrepancies in emotions (variance of the emotional assessment values is high for the tweets in the region) for an observation period.
Identify dominant topics in the tweets identified in steps 1 and 2.
Capture temporal patterns of the evolution of the regions identified in step 1 and 2 including:
Continuity over time
Disappearance / Appearance of new regions
Growth / Shrinkage
Seasonality
Drastic Variations in Emotions in Short Periods of Time …
Convert results found in steps 1, 2, 4 into movies/animations that capture the spatio-temporal evolution of emotions in an observation region (e.g. Texas, US,…) over a period of time (e.g. 5 years, 1 year, 1 month): kind of facilitating (spatio-temporal) data storytelling; similar to:

4. Tweet Emotion Analysis

5. Tweet Analysis

7.
Comment: Tableau seems to be completely crazy about using their tool about Data Storytelling. However, at the moment I do not see any convincing evidence that their tools do anything sensational with respect to data storytelling or with respect to data analytics: unless they present something more convincing evidence people will continue to use R tools, ArcGIS maybe Python tools for Data Science and not Tableau.

8. Display Tools1 for St^2: Bubble Charts
Gap Minder:  
Video:
Bubble Chart r
Data Analysis and Intelligent Systems Lab

9. Display Tools1 for St^2: Bubble Charts
Display Tools for St^2: Density Polygon Trees
proposed by Y. Zhang & Ch. Eick at ACM SIGSPATIAL 2017 Conference r
Data Analysis and Intelligent Systems Lab

10. Display Tools1 for St^2: Bubble Charts
E-R Diagram for Change Analysis Output
from to #
name
longitude
latitude
time
ems
text
C-Predicate
Contains
Tweet
Batch
Belongs-to
BC-relation-ship
C-Relation-ship
C-Predicate
name
from
CC-relation-ship
Spatial
Cluster r to
polygon
ems--avg
den-val
Data Analysis and Intelligent Systems Lab

13. Tweet-Emo-Meter Research
Related: