Data Access, Ownership and Control in Social Web Services:Issues for Twitter Research

Cornelius Puschmann, Humboldt-Universität zu BerlinJean Burgess, Queensland University of TechnologyAxel Bruns, Queensland University of Technology

Merja Mahrt, Heinrich-Heine-Universität Düsseldorf

ICA 2012Track: Communication and Technology

Session: Researching Social Media: Ethical and Methodological Challenges

26 May 2012, Phoenix

“There are also significant questions of truth, control, and power in Big Data studies: researchers have the tools and the access, while social media users as a whole do not. Their data were created in highly context-sensitive spaces, and it is entirely possible that some users would not give permission for their data to be used elsewhere.”(boyd & Crawford, 2012, p.12)

#1Access, control, ownership and interpretation of data are interrelated facets that raise questions of power.

#2Market, legislation, social norms and code are dynamic regulatory forces in social web platforms.

Data

Access (technology) Control (ability)

Ownership (law) Interpretation (competence)

TOS“law”

API“code”defines enables

• founded in 2006 by Jack Dorsey• 140 mio active users• 340 mio tweets per day• source of real-time information on a breadth of issues

from pop culture to politics • increasingly used as a data source among researchers

(e.g. on election prediction via Twitter: Tumasjan et al, 2010, Jungherr et al, 2011, Gayo-Avello, 2012)

• Twitter‘s (future) business model is based on advertising• ad revenue of $260 mio in 2012• sources of revenue:• promoted accounts• promoted tweets• promoted trends

“What‘s yours is yours (but also ours)”

Terms of Service

Twitter Rules

API Rules

“..but only if youknow how to get it”

“Don‘t do what gets us into trouble”

“By submitting, posting or displaying Content on or through the Services, you grant us a worldwide, non-exclusive, royalty-free license (with the right to sublicense) to use, copy, reproduce, process, adapt, modify, publish, transmit, display and distribute such Content in any and all media or distribution methods (now known or later developed).”

“You agree that this license includes the right for Twitter to make such Content available to other companies, organizations or individuals who partner with Twitter for the syndication, broadcast, distribution or publication of such Content on other media and services, subject to our terms and conditions for such Content use.”

“We encourage and permit broad re-use of Content. The Twitter API exists to enable this.”

The TOS

“You will not attempt or encourage others to: sell, rent, lease, sublicense, redistribute, or syndicate access to the Twitter API or Twitter Content to any third party without prior written approval from Twitter. If you provide an API that returns Twitter data, you may only return IDs (including tweet IDs and user IDs). You may export or extract non-programmatic, GUI-driven Twitter Content as a PDF or spreadsheet by using "save as" or similar functionality. Exporting Twitter Content to a datastore as a service or other cloud based service, however, is not permitted.”

“Except as permitted through the Services (or these Terms), you have to use the Twitter API if you want to reproduce, modify, create derivative works, distribute, sell, transfer, publicly display, publicly perform, transmit, or otherwise use the Content or Services.”

API Rules

REST API Streaming APISearch API

• similar to site search functionality• originally a third-

party product• rate-limited• use of Streaming

API for high velocity queries is recommended

• allows interaction with Twitter similar to an individual user (“core” data)• rate-limited• whitelisting was

previously possible, now discontinued

• real-time access to information moving through Twitter• for developers with

“data-intensive needs”

The APIs

• Twitter doesn‘t look to analytics as a source of revenue• providing data is costly in terms of computing resources • analytics are left to companies like Gnip and Datasift• these data resellers have little to gain by catering to the

scientific community or Twitter‘s users

Intermediaries of Data

TwitterData reseller

(Gnip, Datasift)

Large data interpreter

(orga.)

Small data interpreter(individual)

Individual user

Log data

Historical data

Real-time data (all)

Real-time data

(sample)

Actors and Options

• the exact sample size and quality of any data from Twitter is unknown (see e.g. Gnip‘s Power Track) • TOS and API regulate access to Twitter data for

different actors (users, researchers) on different levels (access, control, ownership, interpretation)• for users, the API is the only point of access to

“their” data apart from the web interface• the implicit audience for virtually all services built on

Twitter data are companies• both users and scholars lacking access to high-

performance computing infrastructure are likely to be sidelined by the trend towards Big Twitter Data

Conclusions

Thank you for your attention!

Contact: Cornelius Puschmannpuschmann@ibi.hu-berlin.de / @coffee001

images retrieved from Twitter 1% random sample