This paper presents a study on Twitter use by SJ, the national Swedish train operator. The aim of the study is to investigate how SJ (known on Twitter under the handle @SJ_AB) made use of the platform at hand to communicate with customers during the tumultuous Christmas season of 2010. The paper features an analysis of an extensive data set containing 3,394 tweets tagged as relevant and archived during the winter of 2010/11. Findings show that while SJ are indeed utilizing Twitter to communicate with their customers, the discerned communicative patterns are mostly pertaining to what is described as an “office hour”–approach — making use of the Twitter platform in a way that largely conforms to established routines of organizational communication.
Social media — Private and professional, internal and external uses
Organizations and social media — Internal and external uses
Crisis communication through social media — Case setting
The way that the Internet combines the interactive aspects of telephones and the broadcast potential of traditional mass media potentially facilitates new forms of collaboration between people and organizations (e.g., Shirky, 2008). It follows from this that organizations must learn how to engage in conversations with various stakeholders in the emerging social media landscape, thereby developing uses of social media that purposefully engage said stakeholders in the basic functions of their respective areas of business (Li and Bernoff, 2008). The idea that social media and ICT become instruments of engagement, not simply of broadcast points, highlights what could be labeled as the disruptive nature of social media for organizations. While ICTs have undisputedly become an indispensable part of professional life, individual channels or genres of Internet communication are under scrutiny regarding their usefulness in the context of organizational communication and public relations (e.g., Martin, 2007).
Among such novel Internet phenomena, various applications collectively labeled as social media have recently gained attention among academics and practitioners alike. The question for both groups, though, has been as to whether or not these new technologies, including Facebook, Twitter and YouTube, would have any real business impact , effectively challenging the way public relations professionals carry out their work. As pointed out by Vodanovich, et al. , using Twitter and other social media platforms to indicate one’s current status or exchange opinions about specific topics has almost become the norm for personal as well as for professional purposes. In relation to the latter, the necessity of corporate use of the platform at hand, Jansen, et al. notes that Twitter allows its users to ‘share brand affecting thoughts [...] on a scale that has not been seen in the past’ . It follows from these developments that corporations need to be alert and take measures in order to assess relevant discussions and happenings online.
Recently, it would appear that at least some of the initial skepticism expressed by ICT professionals regarding the merits of various social media has been converted into curiosity — as McKenna puts it, ‘there has been a sea change in the last three months, as Twitter, in particular, takes the corporate world by storm’ . As such, there is a pertinent need to examine the uses of social media services like Twitter in different professional contexts .
This paper presents a study on Twitter use by SJ, the national Swedish train operator. Specifically, we analyze a large data set consisting of Twitter messages (henceforth tweets) dealing with SJ and captured during the tumultuous Christmas season of 2010. A period during which many Swedes travel by train for holiday celebrations, the Christmas season of this year was marred by unusually heavy snowfall, extreme cold and, as a result, numerous delays and train cancellations. Taking the claim that ‘Twitter has been found to be useful for emergency response and recovery’ (Mendoza, et al., 2010) into account, this paper provides a structural study of corporate social media use under pressure. How did SJ make use of Twitter to communicate with their audiences? What patterns emerged from these communications, and what lessons can be learned from these by academics as well as practitioner? As Sweden often scores high on levels of Internet penetration as well as use (e.g., Facht and Hellingwerf, 2011), the country makes for an interesting case study. Moreover, as the bulk of studies on professional social media use have focused on English–speaking countries (e.g., Riemer, et al., 2011), there is a need to study these practices also in different contexts.
The paper proceeds as follows. The next section addresses different uses of social media with a special focus on corporate adoption of such media for stakeholder interaction, including a presentation of the case setting. We then present the research method used in the present study, and move on to presenting the results. Finally, we present our interpretation and address theoretical and practical implications of the findings.
As pointed out by Hogan and Quan–Haase, social media are ‘a moving target’ , making it notoriously difficult to offer one unanimous definition. In the context of professional use, social media can be understood as customer created messages of varying length, related to a specific brand, typically informed by personal experience of that brand and shared online for access by other potential customers (Blackshaw and Nazzaro, 2006). Where a service like Facebook is focused on maintaining an online profile and interacting with fellow users on one particular site, Twitter use involves the sending of ‘short comments usually delivered to a network of associates’ . Twitter users have made use of the flexible nature of the service and developed new, hitherto unforeseen ways of communicating with the service. For example, communication with specific users has been made possible by utilizing the @ character in order to indicate addressivity. Similarly, a message originally sent by one user can be redistributed by another user by means of retweeting (RT in short) — the act of re–sending the message of other users. Following the typology suggested by Kwak, et al. (2010), a tweet can be classified as a Singleton (indicating a message not intended for a specific user/s, nor a retweeted message), a Reply or a Mention (by means of the @ sign followed by a specific user ID) or a Retweet (a redistributed message as discussed above). Tweets frequently also include so–called hashtags, thematic indicators or keywords indicating that the tweet at hand is relevant according to some event, topic or theme. Hashtags are identified by the # character and allows for easy indexing of tweets according to specific interests.
Although initially geared towards leisure time activities, use of social media such as Twitter has evolved and entered more professional realms of use (Nardi, et al., 2004). Indeed, Zhang, et al. points out that ‘the business community has recently become interested in microblogging’ . While Twitter appears to be among the more popular forms of social media when it comes to corporate or business use , it is not the only recent technology to be discussed in a professional context. The next section discusses internal and external use of social media.
Inspired by Milstein, et al. (2008), it appears feasible to differentiate between two different types of corporate social media use — internal use, pertaining to conversations among employees of a specified corporation, and external use, concerning the corporation’s engagement in conversations with external stakeholders.
The use of social media for internal organizational purposes has been studied in a number of different contexts. For example, Zhang, et al. (2010) focused on the early adoption and use of Yammer, a corporate Twitter clone, in the realms of a Fortune 500 company. Employing a mixed method approach (utilizing metadata from microblogging, demographic information, a survey and user interviews), they nonetheless reached somewhat inconclusive results: perhaps not very surprising, users within the company varied in their uptake use of the microblog service. While the respondents could identify benefits of using Yammer, such as being able to stay aware of co–workers’ activities and the possibility to make new connections to more distant colleagues, they also acknowledged the limitations of the platforms. Most notably, the authors identify something they label the noise–to–value ratio — the tendency for useful messages to be hidden behind heaps of messages of no use to the individual user.
Similarly, Zhao and Rosson (2009) performed an exploratory study on the internal use of Twitter at an undisclosed IT company. Specifically, they employed semi–structured interviews and queried 11 participants, each with varying levels of Twitter experience, on their current Twitter practices and on their experiences regarding use of the platform in a professional context. Similar to the study by Zhang, et al. (2010), the respondents here also reported advantages as well as disadvantages with using the platform at hand. Indeed, while microblogs like Twitter might constitute a ‘mechanism for generating virtual watercooler conversations’ , indicating a social potential when used among co–workers, it is also marred by the need for clear boundaries and regulations to deal with work–related and personal content, as well as the need for a sizeable population of users in order for the service to reach critical mass within a specific organizational context.
Although Baehr and Alex–Brown (2010) studied the use of blogs in internal organizational contexts, this particular form of mediated expression bears similarities to the one under scrutiny here. Indeed, their findings were similar to the ones reported by the previously presented studies. While positive effects of corporate blogging could be discerned, such as an increased sense of group cohesiveness and shared understanding of different organizational roles, the respondents also expressed perceived disadvantages related to using blogs, similar to the ones suggested by the studies presented above. The authors also point out that ‘organizations have begun using blogs as networking and information–sharing tools [...] externally for customers and vendors’ . The next section deals with such external uses.
Following Jansen, et al. (2009), ‘there are a lot of possibilities to use Twitter and similar sites for customer relations and branding efforts’ . Moving beyond the internal use of Twitter and similar services for internal uses, the employment of social media to ‘interact in firm–customer dialog’  has become more common in recent years. For example, in 2006, Dell restructured their communication strategy, putting substantial effort into employing novel ways of creating and maintaining relations with their customers (Baehr and Alex–Brown, 2010). Similarly, Starbucks has been heralded as exemplary in their external social media practices, allowing their customers to provide ideas for development of the company as well as the ability to vote on the ideas offered by others, among other things (Gallaugher and Ransbotham, 2010; Jansen, et al., 2009).
While external use of social media services like Twitter is still rare, there are numerous advantages to this practice — if employed properly. Considerable research has focused on the use of blogs — a separate, older and different genre of social media, but arguably similar to the Twitter platform. Asides from actually constituting platforms for corporation to customer dialogue , the blogging platform is also perceived by customers as more conversational than ordinary Web sites, and that this ‘conversational human voice’ was seen as positive by the customers . Such a conversational approach can also come in handy when dealing with negative sentiments posted online (e.g., Stieglitz and Krüger, 2011). As pointed out by Park, et al. , ‘Social media is bringing a major headache to the corporate world because it has been shown to facilitate the spread bad news’. The present study, then, presents a structural approach to assessing the patterns of communication emerging from customer–organization interaction.
As shown above, the advantages of employing social media in organizational settings appear to be plentiful — but there are also disadvantages. Social media can be seen as promising both opportunities and threats , and firms are therefore experiencing a difficult time in navigating the ‘emerging complex, consumer–empowered environment’ , wondering ‘whether social networking is leading the way, or in the way’  of corporate communication strategies. It would seem that a crisis of some sort would constitute an interesting opportunity to stress test such strategies.
Following Sweetser and Metzgar, the ‘shorter statements through a personal/human voice’  offered on social media platforms such as blogs make them ideal channels for crisis communication purposes. These suitable characteristics are also found when dealing with the Twitter platform. Indeed, Mendoza, et al. (2010) point out that Twitter’s mobile functionalities in combination with the potential of retweets to reach wide audiences, the service is characterized by numerous positive aspects when used for crisis communication purposes.
A number of recent studies have focused on Twitter employment during a variety of crisis situations. Much of this research has focused on providing examples of uses, on mapping out “heavy areas” of use on maps or on providing other metrics for Twitter use. For example, Longueville, et al. (2009) studied use of the platform during the widely reported forest fire that took place near Marseille, France in July of 2009. While their sample consisted of a modest 346 tweets, the authors provide a number of descriptives regarding Twitter activity during the critical phases of the forest fire. Similarly, Mendoza, et al. (2010) focused on Twitter use during the 2010 earthquake in Chile, characterizing the activity on the platform during the hours and days following the disaster by providing a number of different metrics. Similar studies on other crisis situations are available, such as Hughes and Palen (2009) on hurricanes and Kireyev, et al. (2009) on earthquakes, all indicating a potential of the channel at hand. Indeed, while online novelties such as the one under scrutiny here can provide new opportunities for corporate–customer communication, social media also bring about tensions regarding openness at the hands of the organization involved as well as a potential loss of message control (Macnamara and Zerfass, 2012).
In this study we turn attention to SJ, the Swedish national train operator, and their use of Twitter, specifically during the hectic Christmas period in 2010. With the holiday season approaching, trains were booked solid in order to accommodate a multitude of passengers. While Swedish winters do indeed tend to be cold, this particular period was characterized by exceptional cold, even by Swedish standards, as well as by heavier than usual snowfall. As a result, severe disturbances in train operation were experienced and thousands of travelers faced delays and even cancelled trains.
Catering to the railway travelling needs of a supposedly IT–savvy country like Sweden, SJ could be said to have established a clear presence online. Their Twitter account, @SJ_AB, has been active since 2009, and they also maintain profiles on a number of other social media platforms, like Facebook (since 2010), YouTube (since 2005) and Flickr (since 2011). As such, while it is difficult to compare SJ to the online activities of large, multinational companies (e.g., Gallaugher and Ransobotham, 2010), we can conclude that SJ appears to offer a multifaceted range of online activities — something that could be expected to play a part in their handling of a weather–related episode like the one under study here.
Gathering online data can be troublesome. While there is an abundance of interesting data available online, researchers need to employ some means or principle of selection or method to “thin out” the data available. Different forms of automated data collection is often employed, but this can be problematic due to data being spread across numerous different platforms and technical storage solutions . As mentioned earlier, content on the Twitter platform can be sorted by means of hashtags — a kind of ‘community code’ (Longueville, et al., 2009), indicating the relevance of a specific Tweet for a specific theme. For the topic at hand, the hashtag of “SJ_AB” (Swedish for SJ AB, the full company name of the Swedish train operator under scrutiny here, http://www.sj.se/) was employed for selection purposes. As such, all messages sent during the selected time period that included the word “SJ_AB” was archived for analysis.
Data for the study was gathered by means of the YourTwapperKeeper application. YourTwapperKeeper is a non–commercial Web crawler focused on the Twitter platform and available for downloading and installation on http://your.twapperkeeper.com/ and has been used for similar forms of data gathering in previous, similar research efforts (e.g., Bruns, et al., 2010; Larsson and Moe, 2012). Specifically, the application provides a list of all Twitter messages tagged or otherwise specified as relevant according to the conditions of the user. The list consists of the Tweet sent, the sender, recipient (if the message sent was directed to another user), time stamp and information on what application was used to send the message. In order to provide a broader scope of the twitter activity preceding and following the Christmas holiday, tweets were archived starting 22 December 2010. Archiving was put to a halt on 15 January 2011, yielding a total of 3,394 tweets.
While this data gathering process has a number of advantages, providing us with Twitter messages relevant for the purpose of the study, the rationale employed is not without its limitations. For example, untagged, potentially relevant messages sent are not gathered using this rationale. Moreover, users might employ the tag at the start of a conversation, but fail to do so as the sending and receiving of messages continues (see Moe and Larsson, 2012). In sum, while the method for data gathering has potential flaws, it was deemed feasible for the study at hand.
In order to provide an overview of the sample, the total number of tweets sent during the specified time period is outlined in an area graph, provided in Figure 1 below.
Figure 1: Tweets sent during the examined period.
The graph separates the tweets sent by SJ (depicted in grey) from the tweets sent by other users, (“passengers”, depicted in black). The vertical axis provides the number (N) of tweets sent during the times specified on the timeline available on the horizontal axis. Figure 1 is characterized by a number of spikes, indicating that most tweets during the examined time period were sent during daytime hours. Besides this point, there are several additional aspects of figure one that need to be dealt with.
First, the dominance of darker shades in the graph indicates that most tweets were sent by passengers. Perhaps not very surprising, it is still worth to point out that even though the passengers are clearly dominant in sending Twitter messages, SJ can be said to at least try to match the stream of incoming messages, as indicated by the gray areas in the figure.
Second, while the stream of passenger messages appears almost constant throughout the examined period, there are noticeable gaps in the data where SJ did not send any messages. As pointed out earlier, most tweets seem to be sent during workday hours. However, as train runs virtually 24/7, including holidays, tweets regarding SJ can be expected to show up afterhours — during times when SJ social media personnel were not working, apparently. The biggest such activity gap on SJ’s part appears during the height of the Christmas and New Year holiday season — while Tweets (albeit comparably few) were sent by passengers between 24 December 2010 and 2 January 2011, no tweets were sent by SJ during that same time period. Similarly, gaps appear during after–office hours and weekends (Saturday 8 January to Sunday 9 January, for example). Prior to these events, however, we notice some of the biggest “spikes” of activity during December 22 and 23 — two days characterized by extensive travelling, and therefore also by increased Twitter use.
Third, the above described “office–hour approach” to social media appears to create backlogs of tweets for SJ personnel. As shown in Figure 1, each period of inactivity on SJ’s behalf is followed by periods of intense activity — as if SJ are trying to deal with the backlog of messages sent during the weekend, holiday or night that has just passed.
While figure one provides an overview of the collected data on a time axis, it does not delve deeper into the various use practices akin to the Twitter platform (i.e., @ messages and Retweets). For these purposes, we analyze the data utilizing the Gephi software package (see Bastian, et al., 2009). Specifically, Gephi is an open source graph visualization manipulation software, available for installation on multiple platforms at http://gephi.org/. We begin with looking at how the possibility to send directed messages by means of the @ sign was used. As described earlier, Twitter users can send directed messages to each other by including the @ character followed by a specific user name in the message to be sent. Figure 2 provides a network graph mapping out the prevalent @ networks in the data set.
Figure 2: @ networks. Graph constructed using the Force Atlas layout available in Gephi.
Figure 2 features a number of nodes, each representing an individual Twitter user. The shade of the node represents what is often understood as the outdegree of each user — a measurement of the number of sent messages. For this figure, darker shades indicate that a particular user has sent a larger number of @ messages. The size of the nodes are determined by the indegree — the number of received @ messages. The bigger the node, the more @ messages were received by that particular user. Straight lines connecting nodes specify unidirectional communication, while curved lines suggest reciprocity in exchanges of messages.
With these interpretational guidelines in mind, one user in particular stands out. SJ_AB, the official Twitter feed for the Swedish train operator, appears as the most active user with regards to both sending and receiving @ messages. Perhaps not very surprising, the node that represents SJ_AB appears in the middle of the graph presented in Figure 2, which indicates its dominant role during the time period under scrutiny. Interestingly, the graph further indicates that rather few conversations appear to take place between users, excluding SJ_AB. Finally, the lack of darker, bigger nodes connected to SJ_AB indicates that rather few conversations went beyond a two–part “question–response” structure. As such, conversations tend to flow from passengers to SJ_AB and back, typically cutting short after the response from SJ_AB has been sent. As the majority of conversations between SJ_AB and other users are depicted as curvilinear lines, this indicates that SJ did indeed play an active part in the majority of conversations it took part in.
Through the practice of retweeting, a Twitter message can be redistributed in several steps, resulting in a disseminating mode of communication. Studies have demonstrated that retweeting is effective to distribute messages from users with few followers (Kwak, et al., 2010), allowing these messages to reach a wider audience. It follows that retweet activity is fundamental as a measure of whose messages are seen as important on Twitter. Once again utilizing Gephi, Figure 3 provides a network map of retweet activity, focusing on the high-end users in this regard.
Figure 3: RT networks. Graph constructed using the Force Atlas layout available in Gephi.
Much like in Figure 2, each node visible in Figure 3 represents a Twitter user. Darker nodes indicate high activity with regards to retweeting others’ messages. Users who are often retweeted are identified by the larger sizes of their corresponding nodes. Line styles are to be interpreted in the same manner as in Figure 2 (see above). Following these parameters allows us to discern several sub–networks within Figure 3. For example, SJ_AB is clearly the central node in one of the biggest sub–networks: as made visible in the top of Figure 3, SJ_AB was retweeted amply during the time period under study. The comparably darker shade of the SJ_AB node also indicates that they perform a certain degree of retweeting, thus redistributing messages sent by others. To the right of and slightly below the network surrounding SJ_AB, the node representing the user malmesjo is clustered as the central node of another sub–network. While the node size of malmesjo is considerably smaller than that of SJ_AB, its shade is darker, indicating a more reciprocal approach to the practices of retweeting. Similarly, smaller networks can be discerned around other users (such as DomainGoogler, TantKakelugn and jmolofsson), all located to the left of and below the SJ_AB node. This indicates that retweet activity appears to have been a more widespread practice between users than that of sending @ messages. Finally, in comparison to Figure 2, Figure 3 seems to present a network consisting of fewer nodes. This indicates that compared to the practice of sending directed @ messages, the habit of retweeting was not employed as much during the time period. As a result, comparably fewer nodes make up the network for retweeted messages.
The study of organizational use of online interactive (social) utilities such as Twitter is undoubtedly of both scholarly and practical importance. Although the focus here is on Twitter, allegedly ‘the world’s second most important social media platform after Facebook’  it is our belief that the conclusions drawn are general enough so as to be applicable to similar or future forms of online communication, more or less akin to the Twitter platform. Similarly, while the focus of our study is on one specific company, other organizations wanting to adopt Twitter, and other social media, to interact with customers and other stakeholders may face similar challenges to those we have observed.
Notions of the popular rhetoric ‘Web 2.0’ (e.g., O’Reilly, 2005; Warr, 2008) is often used to describe a shift towards the Internet in general as becoming more geared towards audience participation of various types. The ‘version 2.0’ of the Internet necessarily presupposes a ‘version 1.0’ of the same. In the case of the Internet, a more traditional, sender–receiver type model might be brought to mind when describing such an earlier version. As we have seen in the analyses presented above, while SJ does indeed have an active presence on the Twitter platform, it does not appear to be as active as its passenger stakeholders or customers. A principal example of this is the tendency for SJ to apparently not have their Twitter account manned and ready for communication with passengers during after hours; late evenings or even nights when their passengers might be experiencing delays or other difficulty. This may be labeled an ‘office–hour approach’ to social media — the organization, in this case SJ, realizes that some form of presence on the novel platform is necessary. Such an approach also signals “bandwagon” effect of sorts — while organizations such as SJ realize the need to maintain an online presence, for example on Twitter, they have yet to find the specific modes of use or even “best practices” for sustaining such activities.
The results regarding the use of @ messaging presented in Figure 2 suggests that SJ is indeed the most active user in the network — perhaps not very surprisingly, but interestingly SJ not only receives a multitude of messages, the organization also displays reciprocity in the uses of the @ character, answering messages and entering into dialogue with their passengers. In studies on social media use by established political actors, researchers have used the term ‘Web 1.5’ (Jackson and Lilleker, 2009; Larsson, 2011) in an attempt to describe what we argue is a similar situation to the one described in this paper — a position in the middle, so to speak, of the initial and allegedly present version of the World Wide Web. Jumping on the aforementioned bandwagon without really being able, or willing, to embrace the culture and expectations of fellow passengers, as it were. While this study cannot provide information regarding the communication priorities of SJ, the practices portrayed here clearly has consequences for how the online presence of the organization is perceived.
Retweeting entails the practice of redistributing messages sent by others. As such, a Twitter user whose messages are often retweeted can be said to hold some status in the network. As evident from Figure 3, SJ indeed appears to hold great status, as its Twitter messages are frequently redistributed in comparison to the other users. While that may be, the fact that users other than SJ appear to be more active when it comes to retweeting might be of interest for future researchers to address. Who are these power users that engage in the network around a specific organization or, for that matter, event? What kind of message tends to get retweeted? While this paper cannot provide specific details regarding these matters, this is indeed a pertinent area for future research.
The results presented above are also of relevance for practitioners, whishing to approach their respective customers or audiences via various social media platforms. The study suggests that companies need to develop a strategy for how to engage with their stakeholders through social media. Such a strategy needs to take into account the culture and normative behavior present in the specific part of the social media landscape one is entering. Certainly, we do not claim that SJ lacks awareness, or even strategy, in regards to Twitter and social media at large. However, it is clear that companies are struggling with how to embrace social media as a platform for stakeholder interaction and conversation. For example, United (Twitter handle @United) declares on its Twitter page that “if you require a specific response,” you should contact its Customer Relations department through more traditional channels. Clearly, sticking to office hours and established communication channels is more aligned with a traditional organizational culture than the one associated with participation in social media. An organization’s social media strategy needs also to be sensitive to the structure of the particular media one is adopting so that, for example, tweeting and retweeting behavior can be tailored to the position and status one wants to achieve within the network. Further research is needed to understand better how such strategy can be formulated and executed.
Finally, while the present study has provided insights into professional Twitter activity of relevance for researchers and practitioners alike, it also has limitations that needs to be duly addressed. First, as touched upon previously, the research design employed here undoubtedly provides us with a “snapshot” (e.g., Brügger and Finnemann, 2013) of a particular moment in time. An expanded sample would have allowed us to make clearer assessments of how the activity described here differed — if at all — during times of no difficulty. As such, a more longitudinal approach to data collection is recommended for future research efforts.
Second, as the focus of this study was placed on providing a structural overview of events occurring during the “snapshot” of time studied, we can say very little regarding the actual contents of the tweets — who is saying what to whom? Indeed, while structurally focused efforts like the one at hand can provide overarching insights into these matters, they are ideally complemented by parallel studies providing “thick” descriptions of the relations traced. As such, the recommendation is made for future research to employ not only quantitative, but also some variety of qualitative methods to gauge these types of empirical material.
Organizations are clearly struggling with how best to adopt social media in their interactions with various stakeholders. In this study of Swedish railway operator SJ, specific attention has been given to the ability of an organization to adopt a communications strategy that ties in with what could be described as the Web 2.0 ethos. Given this perspective, the traditional sender–receiver notion of communication needs to be replaced by an interactive model where the organization participates in a co–creative and responsible manner. Purposeful utilization of online communications requires organizations to develop strategy for how best to engage with the crowd — this may require seeing beyond traditional work–hours and communication behaviors.
In the case described here, we could clearly discern how these more innovative uses of the Twitter service are certainly budding — albeit in an incremental fashion. While SJ does indeed have a presence on Twitter, employing the service to communicate with their customers, the resulting communicative patterns can be interpreted as traces of what has been labeled as a ‘Web 1.5’ style of social media use (Jackson and Lilleker, 2009; Larsson, 2011) — purportedly offering a comfortable segue between the two supposed 1.0 and 2.0 paradigms of Web publication. Indeed, the results presented in this paper indicated that organizations like SJ have started to make their presence known on contemporary online platforms like Twitter — but that they still have a considerable way to go before fully utilizing what could be loosely labeled as the Web 2.0 dictum of openness and ‘harnessing collective intelligence’ (O’Reilly, 2005), arguably ‘the core pattern’  of the publishing rationale under scrutiny.
About the authors
Anders Olof Larsson is a Postdoctoral Fellow in the Department of Media and Communication at the University of Oslo.
E–mail: a [dot] o [dot] larsson [at] media [dot] uio [dot] no
Pär J. Ågerfalk is Professor and Chair in Information Systems in the Department of Informatics and Media at Uppsala University.
E–mail: par [dot] agerfalk [at] im [dot] uu [dot] se
1. Warr, 2008, p. 591.
2. Vodanovich, et al., 2010, p. 711.
3. Jansen, et al., 2009, p. 2,170.
4. McKenna, 2010, p. 22.
5. As suggested by Zhang, et al., 2010, p. 131; Zhao and Rosson, 2009, p. 243.
6. Quan–Haase, 2010, p. 309.
7. Jansen, et al., 2009, p. 2,170.
8. Zhang, et al., 2010, p. 124.
9. McKenna, 2010, p. 23.
10. Zhao and Rosson, 2009, p. 252.
11. Baehr and Alex–Brown, 2010, p. 358.
12. Jansen, et al., 2009, p. 2,186.
13. Gallaugher and Ransbotham, 2010, p. 199.
14. Bonsón and Flores, 2010, p. 25.
15. Kelleher and Miller, 2006, p. 410.
16. Park, et al., 2011, p. 282.
17. McKenna, 2010, p. 23.
18. Gallaugher and Ransbotham, 2010, p. 197.
19. McKenna, 2010, p. 27.
20. Sweetser and Metzgar, 2007, p. 340.
21. Kelleher and Miller, 2006, p. 409; Moe, 2011.
22. Bruns, 2012, p. 1,324.
23. Warr, 2008, p. 592.
C. Baehr and K. Alex–Brown, 2010. “Assessing the value of corporate blogs: A social capital perspective,” IEEE Transactions on Professional Communication, volume 53, number 4, pp. 358-369.http://dx.doi.org/10.1109/TPC.2010.2077491
M. Bastian, S. Heymann, and M. Jacomy, 2009. “Gephi: An open source software for exploring and manipulating networks,” paper presented at the International AAAI Conference on Weblogs and Social Media, at https://gephi.org/publications/gephi-bastian-feb09.pdf, accessed 24 May 2013.
P. Blackshaw and M. Nazzaro, 2006. “Consumer–generated media (CGM) 101: Word–of–mouth in the age of the Web–fortified consumer,” at http://www.brandchannel.com/images/papers/222_cgm.pdf, accessed 24 May 2013.
E. Bonsón and F. Flores, 2010. “Social media metrics and corporate transparency,” Online, volume 34, number 4, pp. 23–25.
A. Bruns, 2012. “How long Is a tweet? Mapping dynamic conversation networks on Twitter using Gawk and Gephi,” Information, Communication & Society, volume 15, number 9, pp. 1,323–1,351.
A. Bruns, J. Burgess, T. Nicolai, and L. Kirchhoff, 2010. “Key events in Australian (micro–)blogging during 2010,” paper presented at the ECREA 2010 conference, Hamburg, at http://www.slideshare.net/Snurb/key-events-in-australian-microblogging-during-2010, accessed 24 May 2013.
N. Brügger and N. Finnemann, 2013. “The Web and digital humanities: Theoretical and methodological concerns,” Journal of Broadcasting & Electronic Media, volume 57, number 1, pp. 66–80.http://dx.doi.org/10.1080/08838151.2012.761699
U. Facht and K. Hellingwerf, 2011. Nordicom–Sveriges Internetbarometer 2010. Göteborg: Nordicom, at http://www.nordicom.gu.se/common/publ_pdf/340_ibar2010.pdf, accessed 24 May 2013.
J. Gallaugher and S. Ransbotham, 2010. “Social media and customer dialog management at Starbucks,” MIS Quarterly Executive, volume 9, number 4, pp. 197–211, and at http://misqe.org/ojs2/index.php/misqe/article/view/301, accessed 24 May 2013.
B. Hogan and A. Quan–Haase, 2010. “Persistence and change in social media,” Bulletin of Science, Technology & Society, volume 30, number 5, pp. 309–315.http://dx.doi.org/10.1177/0270467610380012
A. Hughes and L. Palen, 2009. “Twitter adoption and use in mass convergence and emergency events,” International Journal of Emergency Management, volume 6, numbers 3/4, pp. 248–260.
N. Jackson and D. Lilleker, 2009. “Building an architecture of participation? Political parties and Web 2.0 in Britain,” Journal of Information Technology & Politics, volume 6, number 3, pp. 232–250.http://dx.doi.org/10.1080/19331680903028438
B. Jansen, M. Zhang, K. Sobel, and A. Chowdury, 2009. “Twitter power: Tweets as electronic word of mouth,” Journal of the American Society for Information Science and Technology, volume 60, number 11, pp. 2,169–2,188.
T. Kelleher and B. Miller, 2006. “Organizational blogs and the human voice: Relational strategies and relational outcomes,” Journal of Computer–Mediated Communication, volume 11, number 2, pp. 395–414, at http://jcmc.indiana.edu/vol11/issue2/kelleher.html, accessed 24 May 2013.
K. Kireyev, L. Palen, and K. Anderson, 2009. “Applications of topics models to analysis of disaster–related Twitter data,” paper presented at the NIPS Workshop on Applications for Topic Models: Text and Beyond, at http://www.umiacs.umd.edu/~jbg/nips_tm_workshop/15.pdf, accessed 24 May 2013.
H. Kwak, C. Lee, H. Park, and S. Moon, 2010. “What is Twitter, a social network or a news media?” WWW ’10: Proceedings of the 19th International Conference on World Wide Web, pp. 591–600.
A. Larsson, 2011. “‘Extended infomercials’ or ‘Politics 2.0’? A study of Swedish political party Web sites before, during and after the 2010 election,” First Monday, volume 16, number 4, at http://firstmonday.org/article/view/3456/2858, accessed 24 May 2013.
A. Larsson and H. Moe, 2012. “Studying political microblogging: Twitter users in the 2010 Swedish election campaign,” New Media & Society, volume 14, number 5, pp. 729–747.http://dx.doi.org/10.1177/1461444811422894
C. Li and J. Bernoff, 2008. Groundswell: Winning in a world transformed by social technologies. Boston, Mass.: Harvard Business Press.
B. Longueville, R. Smith, and G. Luraschi, 2009. “‘OMG, from here, I can see the flames!’: A use case of mining location based social networks to acquire spatio–temporal data on forest fires,” LBSN ’09: Proceedings of the 2009 International Workshop on Location Based Social Networks, pp. 73–80.
J. Macnamara and A. Zerfass, 2012. “Social media communication in organizations: The challenges of balancing openness, strategy, and management,” International Journal of Strategic Communication, volume 6, number 4, pp. 287–308.http://dx.doi.org/10.1080/1553118X.2012.711402
N. Martin, 2007. “Keep your eyes on the enterprise: Emails, wikis, blogs, and corporate risk,” EContent, volume 30, number 6, pp. 54–59.
B. McKenna, 2010. “Social networking: The ‘what not to do’ guide for organisations,” Infosecurity, volume 7, number 5, pp. 22–24.http://dx.doi.org/10.1016/S1754-4548(10)70086-3
M. Mendoza, B. Poblete, and C. Castillo, 2010. “Twitter under crisis: Can we trust what we RT?” SOMA ’10: Proceedings of the First Workshop on Social Media Analytics, pp. 71–79.
S. Milstein, A. Chowdhury, G. Hochmuth, B. Lorica, and R. Magoulas, 2008. Twitter and the micro–messaging revolution: Communication, connections, and immediacy — 140 characters at a time. Sebastopol, Calif.: O’Reilly Media.
H. Moe, 2011. “Mapping the Norwegian blogosphere: Methodological challenges in internationalizing Internet research,” Social Science Computer Review, volume 29, number 3, pp. 313–326.http://dx.doi.org/10.1177/0894439310382511
H. Moe and A. Larsson, 2012. “Methodological and ethical challenges associated with large–scale analyses of online political communication,” Nordicom Review, volume 33, number 1, pp. 117–124.
B. Nardi, D. Schiano, and M. Gumbrecht, 2004. “Blogging as social activity, or, would you let 900 million people read your diary?” CSCW ’04: Proceedings of the 2004 ACM Conference on Computer Supported Cooperative Work, pp. 222–231.
T. O’Reilly, 2005. “What is Web 2.0? Design patterns and business models for the next generation of software” (30 September), at http://www.oreillynet.com/lpt/a/6228, accessed 24 May 2013.
J. Park, M. Cha, H. Kim, and J. Jeong, 2011. “Managing bad news in social media: A case study on Domino’s Pizza crisis,” paper presented at the Sixth International AAAI Conference on Weblogs and Social Media, at http://www.aaai.org/ocs/index.php/ICWSM/ICWSM12/paper/view/4672, accessed 24 May 2013.
K. Riemer, S. Diederich, A. Richter, and P. Scifleet, 2011. “Tweet talking — Exploring the nature Of microblogging At Capgemini Yammer,” Business Information Systems Working Paper Series, University of Sydney Business School, at http://ses.library.usyd.edu.au/handle/2123/7226, accessed 24 May 2013.
C. Shirky, 2008. Here comes everybody: The power of organizing without organizations. New York: Penguin Press.
S. Stieglitz and N. Krüger, 2011. “Analysis of sentiments in corporate Twitter communication — A case study on an issue of Toyota,” Proceedings of the 22nd Australasian Conference on Information Systems (ACIS), at http://aisel.aisnet.org/acis2011/29/, accessed 24 May 2013.
K. Sweetser and E. Metzgar, 2007. “Communicating during crisis: Use of blogs as a relationship management tool,” Public Relations Review, volume 33, number 3, pp. 340–342.http://dx.doi.org/10.1016/j.pubrev.2007.05.016
S. Vodanovich, D. Sundaram, and M. Myers, 2010. “Research commentary — Digital natives and ubiquitous information systems,” Information Systems Research, volume 21, number 4, pp. 711–723.http://dx.doi.org/10.1287/isre.1100.0324
W. Warr, 2008. “Social software: Fun and games, or business tools?” Journal of Information Science, volume 34, number 4, pp. 591–604.http://dx.doi.org/10.1177/0165551508092259
J. Zhang, Y. Qu, J. Cody, and Y. Wu, 2010. “A case study of micro–blogging in the enterprise: Use, value, and related issues,” CHI ’10: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 123–132.
D. Zhao and M. Rosson, 2009. “How and why people Twitter: The role that micro–blogging plays in informal communication at work,” GROUP ’09: Proceedings of the ACM 2009 International Conference on Supporting Group Work, pp. 243–252.
Received 15 February 2013; revised 2 May 2013; accepted 8 May 2013.
Detta verk är licensierat under en Creative Commons Erkännande–Ickekommersiell–IngaBearbetningar 3.0 Unported Licens.
Snowing, freezing ... tweeting? Organizational Twitter use during crisis
by Anders Olof Larsson and Pär J. Ågerfalk.
First Monday, Volume 18, Number 6 - 3 June 2013
A Great Cities Initiative of the University of Illinois at Chicago University Library.
© First Monday, 1995-2015.