Authorship and Copyright on Twitter

In 2017, Twitter published significant changes to their Terms of Service, sparking outrage among users about how the new terms affected users. The critique focused on a specific few lines within the terms under "Your Rights" that carefully discuss a shift in content use:

You agree that this license includes the right for Twitter to provide, promote, and improve the Services to make Content submitted to or through the Services available to other companies, organizations or individuals for the syndication, broadcast, distribution, promotion or publication of such Content on other media and services, subject to our terms and conditions for such Content use. Such additional uses by Twitter, or other companies, organizations or individuals, may be made with no compensation paid to you with respect to the Content that you submit, post, transmit or otherwise make available through the services. ("Your Rights;" Twitter Terms of Service)

Many Twitter users responded to this alteration of the Terms by tweeting the implications of these changes on what they believed constituted authorship. Conversations reached folks within the academic Twitter community who were concerned with the effects these changes would have on those who post their writing and art in the medium. Journalistic coverage of these changes, such as Sarah Buhr (2018) and Andrew Griffin (2017), presented these changes as par for the course of social media, arguing that the language pertained primarily to big media corporations needing to share newsworthy video, images, and updates. Since Twitter as a platform functions through widespread sharing of content (often in the form of retweets), such an argument does make sense. Nevertheless, concern remains over how such legal language impacts everyday users without a team of lawyers behind them to protect their content.

Table 3: Tensions in Student IP Heuristic Applied to Twitter
Category Category Attributes
Users Students, instructors, parents, family members, administrators, prospective and current employers, publics, alumni, donors, journalists, government agencies, politicians, bots, trolls, political operatives, predatory actors, platform employees and staff, advertisers
Permissions Platform access is provided for free; instructors compel students to utilize social media platform as condition of participation in course.

Click-wrap agreement where student agrees to platform terms of use

Policies such as end-user license agreements (EULAs), as well as platform-specific copyright and privacy policies, govern use.

Students might create public or private accounts making their contributions more or less visible to those outside of a course.
Inputs Surface contributions: 140-280 character tweets, images, videos, replies, links, retweets, quoted retweets, likes, lists, profile information, hashtags, URLs.

Non-transparent and hidden contributions: Username, hashtags, source/device, tweet ID number, total number of retweets, if reply, screen names of those involved in conversation, number of times tweet has been replied to, profile background image, profile image, followers, statuses, description, friends, geolocation, date, time, geolocation, style, lexicon, IP address, interactivity/behavior within website, time spent logged in/active on website, file types and file metadata, browser used.
Operations Students, instructors, and/or publics might interact by tweeting, replying, liking, quote-retweeting, retweeting, following, unfollowing, listing.

Each tweet/interaction is logged within a mineable database that is publicly available through the Twitter Firehose API to those who write proper script to pull down access to this information.

Twitter may or may not collect/store other types of data/metadata, which are not publicly available.

Twitter or 3rd-parties accessing tweets through the API may perform behavioral analysis and psychometric profiling based on semantic analysis of contributions, hashtags, interactions.

Targeted advertising may be directed to students; algorithms may ensure specific types of content aligning with user tastes, values, beliefs, ideologies reach students.
Outputs Twitter may create psychometric or behavioral profiles on students from user interactions, type of accounts followed, semantic analysis of tweets, types of hashtags used, likes, and/or retweets, which can be sold to third parties.

Twitter, as a platform that supports interactivity, also collects and stores proprietary content, data, and metadata within a proprietary database.

Proprietary algorithms may be trained by making use of this database.

Twitter and third parties making use of the API may rapidly identify trends in news, markets, politics, social interests, memes.

Twitter and third parties might trace and identify social networks that exist within and between users. These may be utilized to reveal social, professional, and/or familial relationships that exist outside of the platform.

Twitter can sell or monetize content, data, metadata, profiles, or insights built on user contributions to third parties.
Gateways Students and users gain ability to author and interact with content in platform. Outside individuals (those without accounts) can search hashtags, visit public accounts, and read content circulated within platform on front-end.

Users can author API commands to access and pull down content, data, and metadata from Twitter firehose stream.

Advertisers can pay for access and ability to target users through psychometric profiling.

In an attempt to make clear to their users where they stand in regard to copyright, Twitter has offered users a standalone copyright policy, a policy that works in addition to the platform's general terms of service. This move is notable because many platforms stick strictly to terms of service or conditions and privacy policies.

Reading over Twitter's copyright policy illustrates that the platform carefully follows provisions regulating content management and circulation on platforms laid out in the Digital Millenium Copyright Act (DMCA), particularly Section 512. Twitter also has a separate sub-policy for trademark, which describes how the platform supports the protection of corporate entity or brand identities. They also have a policy for fan, parody, and commentary accounts—all of which they do not generally consider copyright issues. One critical point worth stressing is that across many of Twitter's policies there is never a clear indication whether the platform considers tweets themselves as copyrightable texts. Only the content that users upload, embed, or link to within the tweets can be protected—that is, if it contains already copyrighted or arguably copyrightable content.

The language in these policies offers relevant takeaways for those of us invested in the impact of copyright upon student authorship within the Twitter platform. For one, the language creates a literacy barrier for most users, which prevents users from fully understanding the legal processes that engender their participation in the platform. Secondly, and due to the first takeaway, a look at the language shows to whom these policies are actually written. Twitter's copyright policy, for example, is directed primarily at corporations who not only have the legal wherewithal to execute a copyright claim over their content, but also have the social and financial power to indebt Twitter's alliances to them. Everyday users with no corporate affiliation retain little to no protection via this policy. Such a policy model, then, enforces copyright within a hierarchical framework, protecting powerful institutions first and foremost—just as Dustin Edwards' (2018) analysis of YouTube's takedown processes illuminated. The unequal distribution of copyright protections over content shared through Twitter hints toward an understanding that Twitter may use their copyright policy as a mechanism for protecting the corporations who fund the platform's financial infrastructure through targeted marketing, paid advertisements, and promoted tweets.

Students and Twitter

What Happens to Student Authorship in Twitter?

Twitter's copyright policy states that the platform respects users' authorial rights to the content they post, but when looking at Table 3, we see that user inputs within the platform are transformed through various operations into outputs such as publicly available databases and proprietary database and user profiles. Students using Twitter are not simply posting tweets, but interacting with the platform in a myriad of ways, many unbeknownst to them. Simply by logging into Twitter, students create a group of data that Twitter processes and collects through their data brokerage system. Of course, these data go beyond what we generally consider authored content. However, the point stands that none of these inputs would be composed or created had the student not logged on in the first place.

To return to the second scenario in TENSIONS, the woman of color who had logged on to Twitter to respond to her reading assignment and tag that content with a course hashtag composed multiple forms of hidden and nontransparent data beyond the tweet that circulated within Twitter, attracting unwanted attention and harmful harassment. These data might include information that could be used to reveal what type of computer she had used, what browser she had used to log onto the platform, her IP address (which is a type of location-identifying information), any other websites she had visited or would visit in the same browser, the duration of her time logged into the platform, what other tweets she viewed and the duration she spent viewing each, the links she clicked, interactions made (likes, retweets, comments), and more. While each of these productive actions are composed by the student, they are not considered authored content in that she does not have the same type of rights to exercise control over how they circulate within the platform as say a songwriter might. Nevertheless, each action becomes attached to her identity, setting off through the invisible data brokerage system that is Twitter's back-end information flow.

What we want to make clear is that there is a difference in the data that Twitter makes publicly available through its API and the other forms of data it collects and aggregates in ways that are treated as proprietary to the platform. Moreover, the amount of data that is linked to even a single tweet is substantive. For instance, consider the various forms of data associated with a tweet our colleague Renee Hobbs authored and tagged with a #COM416 class hashtag in spring 2018 that can be pulled down using Twitter's API.

Figure 11. As a leading figure in IP studies, Renee Hobbs curates an active academic presence on Twitter often using the platform to point colleagues, students, and followers toward information that enriches their understandings of fair use. In this instance, Hobbs has utilized a number of hashtags, including #COM416, #EC534, and #digiURI to link this tweet and content to students, colleagues, and third parties following those hashtags

Twitter's API, then, enables both the platform and those with the technological insight necessary for accessing the public data stream the ability to generate a unique, curated front-end experience for users, while also creating a public facing set of data that developers may query and generalized, permanent data profiles on users for the corporations and third parties with whom Twitter is affiliated. With the awareness that Hobbs has tagged the location of Newport, RI, advertisers in the city may target her with sponsored ads that seek to gain her attention. Based on her interests, she will be prompted to befriend similar users with interests in media literacy and copyright. Tweets she sees in her timeline will be specially chosen for her viewing over others. Moreover, others interested in seeing how Hobbs situates herself as an academic in Twitter might see which users have interacted with the #Com416 hashtag—potentially identifying students with public profiles. Indeed, Hobbs' entire experience in the platform will be created and re-created for her every time she logs on and interacts within it. And, if she is posting strictly for her class, the permanent data profile and curated Twitter experience will reflect the person she has enacted herself to be in the platform as an educator.

Use of Twitter in the classroom impacts student authorship through a complex integration of im/material and asymmetrical forms of circulation with the platform. Tensions arise when all of a tweet's circulatory movements downstream place students in information pathways (to nod to what TyAnna says in our Implications for Pedagogy IP Cast) that will often remain invisible to them, or be revealed in unforeseeable moments of complication or risk. Without the ability to identify the operations, outputs, and gateways of all the information they input to the platform, students will remain engaged in an asymmetrical relationship where they have no control over their authored content.

IP Cast 7: Materiality and Twitter

IP Cast 7. Materiality and Twitter. Jessica, Les, and Tim discuss how the materiality and visibility of user contributions within social media platforms like Twitter create tensions in the management of student-authored IP. Users do not often consider, or directly see, many of the inputs they make within social media platforms as authored contributions. Indeed, inputs might be understood as both content (e.g., images and text), but also the products of user-interactivity (operations) that are stored as data and metadata within a platform. A transcript of the conversation has also been provided.

Rhetorical Velocity

What can we learn about authorship from the circulation of a tweet?

Is a retweet an act or authorship? To explore the ways circulation can rhetorically alter the text an original author composes, we consider the rhetorical velocity (Ridolfo & DeVoss, 2009) of a tweet ostensibly composed "by current US President #45" (Haas, 2018, p. 420) on June 14, 2016, while that individual was campaigning to become the Republican nominee for the 2016 Presidential Election. Rhetorical velocity, as Jim Ridolfo and Dànielle Nicole DeVoss have explained, is "the strategic theorizing for how a text might be composed (and why it might be recomposed by third parties)" as well as "a term that describes…the speed at which information composed to be recomposed travels." That is, rhetorical velocity is both a way of accounting for circulation and recirculation and a type of "inventive thinking" that considers how information composed by one party might be later "recomposed, redelivered, and redistributed" by others. In framing rhetorical velocity this way, Ridolfo and DeVoss challenged computers and writing specialists to consider how future authors might act on and alter the compositions authored before.

Figure 12. This array of three tweets illustrates how a piece of information composed can be taken up by other actors in the future in order to recontextualize the original meaning.

Two days prior to the #45 tweet, there had been a horrific mass shooting in Orlando, Florida, at a nightclub popular with the LGBTQ community, and the candidate apparently sought to frame himself as a champion and ally of LGBTQ rights. By the time this section of the webtext was drafted (March 2018), the tweet had been responded to 851 times, retweeted by 7,200 accounts, and favorited/liked/retweeted by 14,000 accounts. It's important to note that, as distinct interactions, even a singular like, retweet, or response can change the ways that the information contained in the tweet flows through and beyond the platform—can change the very meaning of a tweet—as the original tweet spreads both into new networks and contexts carrying with it newly linked content, data, and metadata.

However, two interactions which followed the initial tweet nearly two years later, on March 23, 2018, are particularly noteworthy because they illustrate how retweeting, as a form of interaction or microcomposing, goes well beyond simply sharing or circulating content. Specifically, these examples demonstrate the types of opportunities for recomposing (Ridolfo & DeVoss) that exist downstream, as future composers alter the meaning of a piece of information by recontextualizing it.

In the first act of recomposition, Kyle Griffin (@kylegriffin1) offered a screen capture of the original #45 tweet from 2016, which appears to look and largely function as a retweet. However, this strategic choice appears to demonstrate that Griffin had sought to avoid a real retweet, which would have further amplified the statistics of Trump's original tweet. The tweet still circulates as a retweet, albeit in a way that doesn't amplify or give credence to the original tweet. Moreover, this "retweet" also repurposed its meaning, as March 23 was a moment when Trump had announced attempts to ban transgender people from serving in the military for the second time during his presidency. Griffin's tweet works, then, to recontextualize the meaning #45's original tweet, suggesting that #45 is not the ally he sought to cast himself as.

A day later, a separate account (since set to private) retweeted Griffin's "retweet," adding the hashtag #thereisalwaysatweet, which is a popular set of curated tweets that points to moments when Trump contradicts a previous statement on a topic or engages in the type of behavior that he had previously criticized others for.

From a rhetorical perspective, each of these compositional acts changed the meaning of the original tweet. In this way, they might be considered unique acts of authorship. Yet, from a legal perspective, it would be difficult to unparcel the compositional contributions @kylegriffin1 or other downstream recomposers have made in their retweet/subtweets from the original. We think that these subsequent contributions impact or add value to the original. Yet we also wonder what types of authorial agency a recomposer might or should have to control or manage contributions that are supplementary and additive to #45's original tweet. Moreover, what stake in authorship/ownership control should or might Twitter deserve because it has provided the platform in which these individuals interface to compose and engage in these richly networked, distributed writing activities? Should we consider Griffin an author? What, precisely, has he authored? What stake of control should he be able to exert over this content? Moreover, how might the curative work that the private contributor made by tagging @kylegriffin1's retweet with a #thereisalwaysatweet be understood as authoring? Certainly, it adds to the ongoing collection of tweets, but should we consider these compositional activities as acts of authorship?



The information and ideas contained in this webtext are not intended to be understood as legal advice, but rather as an exploration of the potential tensions that may exist between how authorship functions as a legal concept and how authorship is practiced and theorized in educational contexts.

Webtext design adapted from © Escape Velocity by HTML5 UP under a Creative Commons CC BY 3.0 license.