INTRODUCTION

Hitting middle age never felt so good: introduction to the AmericanSociological Association Communication and Information Technologiessection 2013 special issue

Jennifer Earla* and Katrina Kimportb

aSchool of Sociology, University of Arizona, Tucson, AZ, USA; bAdvancing Standards in ReproductiveHealth (ANSIRH) program, University of California San Francisco, San Francisco, CA, USA

(Received 3 February 2014; accepted 3 February 2014)

In 2013, the Communication and Information Technologies section of the American SociologicalAssociation (CITASA) hit a milestone: we had the largest membership total in section history at375 members. Just as those membership figures suggest the maturation of our section – as well asthe growing importance of topics we collectively study to sociology and to the interdisciplinaryexamination of communication and (new) media – as Guest Editors of this special issue, we sawthat same maturation, vibrancy, and diversity in the set of papers submitted for consideration forthis issue. We received a wonderful set of papers to review, with those included in this issue repre-senting the best of that crop. We also realized how far the intellectual tentacles of CITASA reachas we worked to identify reviewers (to whom we offer our deep thanks for their service) – it wasamazing to see how broad our collective expertise has become over time.

The eight articles that we ultimately accepted represent the best work from our section thatwas presented at the 2013 annual meetings of the American Sociological Association. Theyalso aptly chart three key developments that we think characterize current research on communi-cation and digital media and point toward future avenues of exploration: (1) the maturation ofwork on measurement; (2) continued work on understanding user behaviour; and (3) researchon social media. Below, we briefly comment on each key development and introduce readersto the articles representing that area in this special issue. In the Conclusion, we make suggestionsfor what a promising research future might hold for us collectively.

Maturation of measurements

Three articles in this special issue mark the maturation of measurement in the study of communi-cation and digital media. When research on digital media was in its earliest stages, scholarsstruggled with how to measure and study the dynamics related to new media. One could thinkof the field as being divided into two methodological halves: (1) for scholars who were interestedin how users adopted or used technologies, basic methods were readily adaptable, such as randomdigit dialing surveys (Hampton, Sessions, & Her, 2009; and more recently online panels,Wojcieszak & Mutz, 2009), participant observation (Beyer, 2011), and interviewing (Earl &Schussman, 2003; Schussman & Earl, 2004); and (2) for scholars interested in what content

© 2014 Taylor & Francis

*Corresponding author. Email: jenniferearl@email.arizona.edu

Information, Communication & Society, 2014Vol. 17, No. 4, 391–397, http://dx.doi.org/10.1080/1369118X.2014.891635

was online and/or the structural characteristics of that content, basic sampling problems existed.While it was straightforward to randomly sample people, or to observe social spaces (even if thatrequired a few new observational tools online), it was not as clear how random sets of websites onparticular topics could be identified, let alone entire populations. As a consequence, a great deal ofearly work in the field focused on case studies where online content, such as social movementwebsites (della Porta & Mosca, 2005), were non-probabilistically sampled.

These methodological differences, in turn, led to different growth rates around differentresearch questions. For instance, questions about access-based versions of the digital divideand broadband divide could be addressed with surveys, enabling research on this topic to flourish(DiMaggio, Hargittai, Neuman, & Robinson, 2001; Katz, Rice, & Aspden, 2001). Likewise,research on uses of technology grew vigorously (Flanagin et al., 2010; Hampton, 2003; Hargittai& Hsieh, 2010).

But, research on online content struggled to develop alternatives to case studies. One initiallypromising technique for creating larger catalogs of sites capitalized on hyperlinks (Thelwall,2004) to establish communities of shared interest to study (Garrido & Halavais, 2003). Whilea number of scholars have used these techniques, link-crawling techniques have been slowerto gain traction in many areas of sociology because of nagging theoretical questions about thesocial meanings of links (Ackland, 2009). For instance, little is systematically known abouthow website creators choose to establish links, how often those links are updated (and so howconnections can be understood temporally), and whether social competitors create disconnectedniche communities. This has created problems for studies based on hyperlinks because the theor-etical underpinnings of the set of sites created is certainly socially structured but in ways socialscientists don’t yet fully understand.

Fast forward to the present and some of these basic methodological disparities have dissi-pated. There are now multiple techniques for drawing random samples of websites on particulartopics (Earl, 2006, 2013; Earl & Kimport, 2011; Earl, Kimport, Prieto, Rush, & Reynoso, 2010;Stein, 2009). The dual shifts toward platform-specific research (i.e. research on Facebook,Twitter, etc.) and the shift toward ‘big data’ have also been boons for researchers interested inonline content. Within these bounded platforms, it is sometimes possible to build on big dataadvances and collect data on a significant share of the population, making sampling less essentialfor economizing on research resources and less necessary, in some instances, for reducing poten-tial selection bias. And, ingenious uses of online content continue to be developed (Bail, 2012).Meanwhile, survey research has also grown, benefitting from the creation of online panels.

We argue that greater resolution in many of these basic methodological debates is allowingresearch on digital media to begin a new chapter in which a larger number of scholars canpush forward with research questions focused on how we refine our methods and measurements.We see this as a lovely maturing shift in our collective scholarship, as scholars join to refine ourmeasures and measurement techniques in the hope of producing the most rigorous research poss-ible. We are not the only ones to notice this shift in scholarship: Neal Caren recently edited anissue of Mobilization (December 2013) on methods in social movement research that featureda number of articles on online data collection and measurement.

While this special issue is not alone in foregrounding the field’s methodological maturation, itdoes feature three articles that we think will significantly contribute to this cause. Hampton,Appel, Dadlani, Dwyer, Kitzie, Matni, Moore, and Teodoro (this issue) examine the veracityof social networks measures that are commonly used in research on information and communi-cation technologies (ICTs). The Internet Social Capital Scales (ISCS), first developed byWilliams(2006) and then revised by Ellison, Steinfield, and Lampe (2007), have been widely influentialsocial network measures. But, Hampton et al. argue that the original scale and its derivatives actu-ally tap constructs that are related to social networks, such as tolerance, community involvement,

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and trust. The authors compare these commonly used measures to more structural social networkmeasures created through the use of name, position, and resource generators; they find that thedifferent measures do not converge. Hampton et al. warn that using scales such as ISCS andits derivatives can lead to incorrect interpretation of findings as scholars attempt to tie social net-works (which ISCS and its derivatives don’t directly measure) to various social outcomes. We seeHampton et al.’s contribution as a wonderful example of refining common and importantmeasures in our field. As importantly, we see this article as using better measurement to makeimportant gains in theoretical precision and clarity.

Blank and Groselj (this issue) make a similar move in terms of building better measures tobuild better theory: they critique standard metrics for measuring Internet usage, arguing thatsuch metrics tend to conflate multiple independent dimensions of Internet use. Specifically,Blank and Groselj argue that previous studies describing or analysing Internet use have often con-flated the amount (i.e. length of time online), the variety (i.e. how many different kinds of activi-ties people do online), and the specific types of activity (e.g. online shopping; online gambling).The authors argue that these are three orthogonal dimensions of Internet use that should be used asindependent predictors and/or as discrete dependent variables, depending on the goal of the analy-sis. They discuss central tendencies in each using data on a British random sample. Their analysesalso reveal that for survey researchers for whom every question is costly, there are ways to reducethe types of usage measures to key indicators of each type, allowing theoretically meaningful ana-lyses with less costly survey lengths.

While Hampton et al. and Blank and Groselj are both concerned with improving long-stand-ing measurement techniques used in research on ICTs, Rojas, McKelvey and DiGrazia (this issue)raise issues with very new measurements. Specifically, Rojas et al. have two methodological con-cerns: are all forms of Twitter mentions the same (i.e. free text mentions, @ mentions, and # men-tions), and does one of the measures work better in predictive analytical analyses of larger socialpreferences? In their study, the authors examine Twitter mentions of US congressional candidatesduring the 2010 election. On the one hand, they find that free text mentions, @ mentions, and #mentions are not interchangeable: users with varying skills levels use these mention styles atdifferent rates and users vary in how they combine these mention styles in ways that suggest pur-poseful choices. This is a critical insight for the surge of research on Twitter. On the other hand,they find that only free text mentions were predictive of vote tallies in the elections. This suggeststhat whether one is using mentions in post-hoc analyses or predictive ones, it is important to dis-criminate between different types of mention styles.

Understanding how people use technology

A second key development in the field of communication and digital media that the articles inthis special issue represent is a focus on understanding how people use technology. A firstprincipal in research on the relationship between technology and society is that technologiesdo not fully determine their own uses and often only very partially do so. For instance, itis not inevitable that someone will use a technology according to its instructions, or evenfor the purpose its creator and/or manufacturer imagined. Indeed, many a page has beenspent on arguments against technological determinism. For instance, in our own work, wehave argued that Internet-enabled technologies create certain key affordances (Earl &Kimport, 2011), which users may recognize and use, may not recognize, or may recognizeand choose not to use.

Several articles in this special issue implicitly argue against technologically deterministicclaims, revealing instead how human interpretation and the actions/uses of technologies(whether hardware or software) are critical. Restivo and van de Rijt (this issue) show that creating

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badges or other technological rewards for activity will not always motivate action. More specifi-cally, prior research has shown that giving ‘barnstars’ (i.e. peer-awarded badges or rewards) tovery active editors on Wikipedia increased their subsequent contributions. However, in theirstudy, Restivo and van de Rijt find that awarding these same informal digital rewards to onlysomewhat active editors does not increase participation. In fact, it had quite theopposite effect: not only did these informal rewards not increase editing activity; the rewardsseemed to hasten the exit from editing altogether. When read through the lens of technologicaldeterminism, it appears that creating systems of informal rewards does not guarantee positivereturns and may even have markedly different results on different user bases within an onlinecommunity.

Similarly, Sanders (this issue) shows that technologies are not silver bullets to social problemsin her examination of the interoperability of emergency response systems. During the emergencyresponse to the 9/11 attacks, a number of first responders perished because they could not effec-tively communicate with one another. Many within emergency services saw this as a purely tech-nological problem: the hardware and software used in emergency response systems was notinteroperable across different kinds of agencies (e.g. fire, emergency medical services, andpolice) and across different jurisdictions (e.g. police in one city could not communicate easilywith police in another city). Hoping a technological solution could easily save lives in thefuture, a massive amount of money was invested in developing and distributing interoperableemergency communication systems. Unfortunately, as Sanders shows, the ‘making’ of interoper-ability is only partly technological: varying laws and social norms about which agencies can haveaccess to information and/or share information significantly impact the real flows of information.Different perceptions about who ‘needs to know’ what information shape information flows as dodifferent constructions of professional roles and duties. Indeed, her research reveals that interoper-ability is not something that is engineered so much as something that can be afforded throughtechnology but actually built through social interaction.

Understanding social media

Finally, several articles in this special issue speak to the burgeoning attention to understandingsocial media by scholars of communication and digital media. That social media are becomingan important part of the online landscape is an understatement. Although it has historicallybeen the case that instrumental computer routines were hijacked for social purposes, the tidehas shifted such that a large number of online platforms are now built primarily to contributeto sociality. Understanding how people use these social media and the effects of people’susage of social media are becoming critical questions. In addition to Rojas et al.’s examinationof Twitter, three other articles in this issue speak directly to questions of import about socialmedia.

First, Davis and Jurgenson (this issue) connect to two themes running through the issue: (1)the importance of understanding user practices; and (2) the increasing importance of studyingsocial media. Like Sanders and Restivo and van de Rijt, Davis and Jurgenson argue that usersof social media are affected by its design but not beholden to it. They focus on the blurring ofsegmented identities online. As any Facebook user is aware, some platforms are built in waysthat push an individual’s social networks and segmented identities together. Family members,old friends, new friends, colleagues, and acquaintances are at risk of virtually interacting withone another and exposing different facets of your identity to one another. Davis and Jurgensonnote that just because Facebook and other platforms are engineered to encourage such ‘contextcollisions’ does not mean that users accept them. The use of the so-called Fakebooks in whichindividuals keep multiple Facebook accounts so that they can still segment their online identities

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by audience is but one example of the many ways users manage to limit or avoid engineeredcontext collapse.

In addition to connecting with themes about the insufficiency of deterministic accounts, Davisand Jurgenson also remind us that social media are pushing us to ask new questions and developnew theoretical constructs to understand the activity that is playing out in these sites. While newtheoretical innovations can rarely be spun out of entirely new cloth (e.g. the authors also use affor-dances as a way to understand technologies’ impacts), their article shows that new concepts suchas context collapse, context collision, and context collusion are necessary for understanding per-sonal identity and its management in social media.

Tufekci and Brashears (this issue) examine variation in the extent to which people feel thatonline interactions are vividly social encounters. Exploring the new concept of ‘cyberasociality’,the authors argue that scholars must not only examine whether people use social media but mustalso analyse differences in how they use it. Their findings show that there is an underlying dis-position toward online encounters that varies and affects how people use online platforms, butit is independent of offline sociability, personality characteristics, experience with technology,and cohort membership. This implies that individuals who do not enjoy online social encountersmay be at a disadvantage in the digital age, given the ubiquity of social media usage in creatingand maintaining relationships.

Haight, Quan-Haase and Corbett (this issue) offer a new twist on the extensive body of litera-ture that has examined the evolving digital divide, arguing for attention to variation – and a poten-tial divide – in the use of social networking sites (SNS). Using data from Canada, whosegeography and population distribution make it a rich case for exploring digital divide issues,they find that age, education, and gender structure the usage of SNS, with women and youngadults using SNS more, but people with high school educations use SNS less often. Their findingsalso connect with the theme of 2013 American Sociological Association Annual Meetings fromwhich all articles were drawn: ‘Interrogating Inequality: Linking Micro and Macro’.

In reviewing the submissions for this special issue, many of which also touched on ‘digitaldivides’ and connected to the larger meeting theme on inequality, we were forced as Editors toconsider the theoretical meaning of digital divides, particularly whether there is a meaningfuldifference between distributions of behaviours caused by social inequalities versus distributionsof behaviours caused by a range of social forces, including personal preferences, perceived utility,and inequality. For instance, as work by Rice and Katz (2004) has shown, there are some individ-uals who do not wish to use the Internet and would not do so even if access were offered to themfor free. To consider these individuals as suffering from an access-based digital divide is question-able even though other individuals still do lack the financial means to gain basic Internet access,let alone broadband access. In the first instance, it is difficult to classify the realization of a per-sonal preference as a meaningful inequality, while it is quite easy to see how geography (e.g.living in rural areas), income, education, etc. create structural inequalities in access. Haightet al. tackle this issue in their study by showing that income is still a strong predictor ofaccess. We suspect, though, that future research will need to increasingly consider that therewill be some individuals who could gain access but choose not to. Understanding where todraw a theoretical line around distributions and divides will be increasingly important in suchinstances.

Likewise, individuals vary in the extent to which they use the Internet, as Haight et al. andBlank et al.’s contributions to this issue show. As Hargattai (2009) and Hargittai and Shafer(2006) have found, some of these differences may owe to differences in skill, which one caneasily imagine are tied to educational inequalities and can be seen as stratification-based‘divides’. However, some differences in whether and how people use the Internet for differentpurposes are likely due to personal preferences and individual needs, making it hard to know

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the extent to which differences in usage are produced by inequalities versus being produced by amix of other factors. We think that the work of Haight et al. is important to unraveling the deter-minants of digital distributions, making it easier to assess what variation appears attributable tostratification and what appears attributable to other factors.

What the future may hold

Although we have endeavored to showcase both the best work from CITASA and the best workon important, contemporary research issues, we believe that each of the areas highlighted in thevolume requires considerably more research attention. In the case of methods, for example,although it is very promising to see so much recent research on methodological refinements instudies of ICTs and their usage, there is much left to be done in this area. Moreover, as thepromise of big data continues to tempt analysts with larger and larger datasets, it will be evermore important to ensure that the theoretical connection between question and data remain inlockstep coordination. Even where big data is not concerned, more areas would benefit from amore concentrated focus on measurement. Likewise, as new technologies are developed, it willcontinue to be important to examine how people actually engage those technologies, as usersoften defy engineering and use technologies in surprisingly clever and sometimes even surpris-ingly odd ways. It is the social structuring of those uses – and their consequences – that must con-tinue to draw researchers’ attention. We look forward to the growth, engagement, and newdevelopments these and other recent ICT research will surely spur, as the field and theCITASA section embrace our middle-age and head toward our ‘golden’ years.

Notes on contributorsJennifer Earl is a Professor of Sociology at the University of Arizona and Director Emeritus of the Center forInformation Technology and Society at University of California, Santa Barbara. Her research focuses onsocial movements, information and communication technologies, and the sociology of law, with researchemphases on online protest and social movement repression. She is the recipient of a National Science Foun-dation CAREER Award for research from 2006-2011 on Web activism and a member of the MacArthurResearch Network on Youth and Participatory Politics. She has published widely, including an MIT Pressbook, co-authored with Katrina Kimport, entitled Digitally Enabled Social Change.

Katrina Kimport is an Assistant Professor at the University of California, San Francisco. Her researchfocuses on gender, sexuality, and social movements. Dr. Kimport’s work has been published in the AmericanSociological Review, Gender & Society, and Symbolic Interaction. She is the author, with Jennifer Earl,PhD, of Digitally Enabled Social Change: Activism in the Internet Age (2011, MIT Press) and of QueeringMarriage: Challenging Family Formation in the United States (2014, Rutgers University Press).

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