Mining Climate Change Awareness on Twitter

University of Vermont EPSCOR. Burlington VT, USA

Ahmed Abdeen Hamed, Ph.D.

Asim Zia, Ph.D.

Authors

Dr. Ahmed A Hamed Dr. Asim Zia

Motivation

Public opinions are powerful tools

Identifications of weaknesses and strengths

Better educating for the general public

Understanding response to decisions

Making new policies and decisions

http://thebridge.agu.org/thebridge/files/2013/10/pollinggraph.gif

In the UK, Leorenzoni et al. studied how public perceives Climate ChangeIn Japan, Sampie et al. analyzed newspapers for public opinion on Global WarmingIn the US, Semenza et al., designed surveys to compare individuals live in Portland OR vs Houston, TX

Background Research

Why Twitter?

The place for honest, short, to the point opinions, scary

Very large content connected to seasons, events

Easy APIs which makes it attractive to mine

Various content devices to measure Words Hashtags Links Impressions

Mining For

Climate Change

We need a set of terms that highly represent

Climate to search Twitter for

We need to rank the terms according to their

importance

We need an objective methods of ranking

We need a notion of ground-truth to compare

against

Ground-Truth

A set of terms :

Carefully selected (TF-IDF)

Closely related (Bigrams)

From an authentic source (Nature Climate Change)

Ground-Truth

Ground-Truth NetworkTF-IDF features + Bigrams

Twitter Bigram Network

Using the TF-IDF Features from Nature Climate Change

Searched 72 million tweets dataset

Constructed Twitter Bigram Network (TBN)

Weights assigned based on the frequencies of bigram

Measured PageRank for each term

PageRank Network Analysis

For each term in the GTN we measured its PageRank

For each term in the TBN we measured its PageRank

Compared Ranks of the same term in the two networks

Comparison Results

TBN

• Generic terms (bigger size)

• Not directly related

• Some related terms (smaller size)

GTN vs TBN PageRanks

Insights

Words are not the only textual features

The social language differs from the academic

Hashtags are very common on Twitter/Facebook

Social impressions (Likes, RT, Shares, Replies, Mentions were not considered)

Sentiments and emoticons were not considered

Investigating Hashtags

Searching tweets for hashtags composed of bigrams

Performing Association Analysis experiments

Using Confidence as a measure of awareness

Surprising Analysis

Conclusions

There is indeed climate change awareness on Twitter

#ClimateChange hashtag #1

Compound hashtags are highly ranked thank single

Still there are missing terms from the big picture #Carbon #CarbonOffsets

Conclusion and Future

There is much awareness on Twitter

Awareness is general but not technical

Hashtags represent a very important element in measuring public awareness

Future: Studying events Combining Sentiments Time series analysis

Acknowledgement

This research is funded by Vermont EPSCoR Award EPS-1101713

Authors thanks the following for their efforts: Alexa Ayer of UVM Rubenstein collecting the

data Dr. Ilan Kelman for the valuable discussions Dr. Ibrahim Mohamed for the visualization and

analysis insights

ahamed@uvm.edu