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You Tweet What You Eat: Studying Food Consumption Through Twitter

Sofiane Abbar, Yelena Mejova, Ingmar Weber Qatar Computing Research Institute

사용자 경험 연구실 유혜수

Understanding Health Through Online Behavior

서울대학교 융합과학기술대학원

Abbar, Sofiane, Yelena Mejova, and Ingmar Weber. "You tweet what you eat: Studying food consumption through twitter." arXiv preprint arXiv:1412.4361 (2014).

2015- 2 Lab Meeting

Authors Keywords: ACM Classification Keywords:

Dietary Health; Obesity; Food; Twitter; Social Networks

Content Analysis and Indexing; Online Information Services; Life and Medical Sciences; Health

-Sentiment Analysis

-Social Media

-“You Are What You Eat”

* Questioned myself: Am I destined to read?

-Understanding Health Through Online Behavior

Why This Paper?

Fun Fact

Most tweeted food in US

on top of which is PIZZA!

Average caloric values

Sofiane Abbar, Yelena Mejova, Ingmar Weber

-Qatar Computing Research Institute

“We examine the potential of Twitter to provide insight into US-wide dietary choices by linking the tweeted dining experiences of 210K users to their interests, demographics, and social networks. We validate our approach by relating the caloric values of the foods mentioned in the tweets to the

state-wide obesity rates, and link this data to societal and economic factors, such as education and income. Finally, we address the somewhat.controversial issue of the social nature of obesity by inducing two social networks using mentions and reciprocal following relationships”

Authors

Background

Method

Data

Build a model to predict county-wide obesity and diabetes statistics based on a combination of demographic variables and food names mentioned on Twitter

Link the data to societal and economic factors (education and income)

Address somewhat controversial issue of the social nature of obesity by inducing two social networks

Summarization

• Social media is notorious for providing its users with a means of documenting the minutiae of their daily lives, including their dietary choices

201K users in the US Tracked 50 M tweets This data allowed them to consider - nutritional value of the foods mentioned in these tweets, demographic characteristics of the users who tweet them, their interests, and the social network induced by their interaction

Food - Integral part of lives, cultures and well being - Major interest to public health

Collection of daily nutritional data involves detailed and periodic surveys -> limited in scope & reach

• Twitter: a potential to provide insight into US-wide dietary choices by linking the tweeted dining experiences

Relate the caloric values of the foods mentioned in the tweets to the state wide obesity

Significant Improvement on HCI

DATA

A large scale analysis of 201K Twitter Users in the US

Consider the nutritional value of the foods mentioned in the tweets - demographic characteristics of the users who tweet them, their interests, and the social network induced by their interaction

50M tweets were collected through the Twitter Streaming API

Duration: 2013 Oct 19 - 2013 Nov 29

Selected all geo-tagged & american tweets = 892 K tweets posted by 400K users

Improve the detection of food- related tweets - Examine 1000 most frequent terms - Handselected terms unambiguously related to food - Crowdsourcing (Crowdsourcing platform) - Published a total 2157 tweet examples

You Might Wonder…• Is data sensitive enough to pick out more personal dietary variations?

• 2010 US Census - demographic information • Extrapolate users’ gender using their screen names, characterise users’ zip code as

being either urban and rural

• Does social network influence personal dietary habits of users? • Traditional Surveys • Social networks = Network structure

• Urban and Rural

Chracterizing Users - Income, Education and Gender

DATA

Interesting point of view: it clearly shows us how much information can be inferred from our data available online (even if it isn’t very exact). For example, in order to assess the sensitivity of data related to more specific personal dietary variations, the scientists used the demographic information from the 2010 US Census. Based on this data, they extrapolated the gender information of Twitter users using their screen names only (!). User-provided ZIP codes were used to classify particular persons as being either urban or rural.

Distinguishing foods between uses in rural and urban areas

DATA

Discussion & Future Work

Using data from social media to study sociological phenomenon and to “nowcast” variables has both advantage and disadvantages

Big Data Analysis: High precision Advantage - time and timeliness - Hundreds of thousands of users can be obtained at relatively low costs - Analyzed in a matter of days, or even hours rather than weeks/months

for comparable surveys

Qualitative - Availability of network information - “homophilly” : social mechanisms

Conclusion

A large scale study of Twitter sphere Monitored US-wide nutritional behavior Daily food #tweets = predictive of the national obesity & diabetes Calories tweets are linked to user interest & demographic indicator

Conclusion

More needs to be done: -develop sensitive and accurate tools for user characterization -Twittter = documentation of users’ interests, opinions, and behaviours -this studies show another example of the potential Twitter has for public health research

Targeting Twitter users with a particular behaviour could be a promising step for interventions such as public health awareness campaigns

Future Works

Take Away Messages You Might Wonder…

• Is data sensitive enough to pick out more personal dietary variations? • 2010 US Census - demographic information

• Extrapolate users’ gender using their screen names, characterise users’ zip code as being either urban and rural

• Does social network influence personal dietary habits of users? • Traditional Surveys • social networks = network structure