Who disseminates academic library information on Twitter?
The purpose of this study is to investigate information dissemination by academic libraries through an analysis of retweet users on Twitter. Academic libraries have posted a variety of information for their patrons on Twitter; however, we know little about who has an interest in academic library tweets and to whom the information is disseminated. To this end, we explored a network of academic libraries by analyzing categories of users who are involved in retweet activity. The results show which user groups disseminate academic library information. We collected 571 retweets and 506 retweet users from 10 academic libraries' Twitter accounts, and categorized them into 12 groups. The results indicate that the primary groups disseminating the tweets of academic libraries are units within universities and students.
Academic libraries adopt new technologies to improve the quality of services and interact with users. Social media technologies such as Twitter have been part of library services for more than several years (Bejune & Ronan, 2008; Farkas, 2007). Such tools are used to share information with users as well as to interact with them through these tools which are already part of the users' information behaviors. Academic libraries post a variety of content on Twitter including announcements, service descriptions, subject information, and news (Aharony, 2011; Phillips, 2011; Stuart, 2010).
The use of Twitter in academic libraries has increased, however, some academic libraries have no clear published objectives for using Twitter or other social media. However, previous research conducted has included content analysis of tweets that resulted in categories of tweets of the information provided to virtual users through Twitter (Aharony 2011; Honeycutt & Herring, 2009; Loudon & Hall, 2010; Stuart, 2010). Little is known how that information is used by their patrons. Twitter has several quantitative indicators measuring the status of accounts. The number of followers, however, does not indicate how successful or popular Twitter accounts are because many of them could be inactive users (Huberman et al., 2009). Thus, qualitative measures such as the types of followers and how the followers interact with library Twitter accounts are suggested to better understand the use of Twitter (Cuddy et al., 2011).
In this study, we focused on retweet users to filter the inactive users from the followers and to include users who interact with library Twitter accounts even though they do not follow the accounts. Retweet is one of the features which enables users to disseminate their information to additional people on Twitter. Academic libraries' tweets can be retweeted by any Twitter user, and libraries sometimes relay authoritative information from other sources to share with their followers. A positive feature of using Twitter is that any Twitter user can follow any account and retweet any tweets, if they are not restricted.
We examined the users who had an active interest in academic library messages on Twitter in order to know by whom library messages were disseminated. This study revealed the types of users disseminating academic libraries' information on Twitter.
We selected ten academic libraries based on the following criteria: libraries in the top 100 universities (U.S. News & World Report, 2012) which have Twitter accounts. The numbers of tweets, followings, and followers were examined, and the selected academic libraries' Twitter accounts exceeded the averages for each of these three categories. Based on Suh et al.'s (2010) study, indicating that the number of followers and followees affect retweetability, we used these criteria in order to select samples having more retweet data. If the holding organizations have more than one library, Twitter accounts which represent the main libraries were selected to balance the characteristics among specific libraries. We investigated Twitter accounts between Feb 15–21, 2012. Among the 100 university libraries in the sample frame, 66 had accounts for their main libraries, 11 did not have accounts for their main libraries, and 23 did not have any accounts for their libraries. Table 1 shows the average, median, maximum, and minimum numbers of the 66 main libraries' accounts for the three categories.
Table 1. Top 100 Academic Libraries' Twitter Data
Retweet data of the selected ten academic libraries were collected from the timeline of each account. After collecting all tweets from the timelines, retweet data were identified by the RT button mark, and the conventions such as “RT,” “via” on each tweet. The 571 tweet data from January 1, 2011 to March 30, 2012 were included in the analysis. Information flow is displayed by using Gephi1 software, an open source networks visualization platform.
Users who were involved in the retweeting of 571 tweets were analyzed through their profile information which is publicly available on a user's account. We identified 506 users from the retweet data, and they were categorized manually into 12 groups according to individuals or organizations, and their roles and jobs: Information professionals, Librarians, Libraries, Local organizations, Other professionals, Professional organization, Publisher, Scholar, Students, University organizations, Hobbyists, and Others.
The 12 groups are defined as follows: The ‘Information professionals’ group includes individuals who are curators, archivists, library vendors, writers, and editors, and excluded librarians. The ‘Librarians’ group includes individuals who work in any library setting. The ‘Libraries’ group includes representative accounts for library institutions. The ‘Local organizations’ group includes accounts which provide local news, information about business, and real estate. The ‘Other professionals’ group includes individuals who have professional positions in various fields. The ‘Professional organizations’ group includes accounts for the American Library Association (ALA), official groups of specific people such as political parties, foundations, and charities. The ‘Publishers’ group includes accounts which provide official information such as news, magazine, and websites related to information technology, and database vendors. The ‘Scholar’ group includes individuals who are educators, or research professionals. The ‘Students’ group includes individuals who are studying at a university or college including undergraduate and graduate levels. The ‘University organizations’ group includes accounts from universities, department, and academic offices, except for university libraries. The ‘Hobbyists’ group includes individuals who describe their various interests for daily life such as music, sports, movies, and food, but do not mention an area of expertise. The ‘Other’ group includes those who do not have profiles or provide too little information to classify them.
Table 2 shows the groups of retweet users who relay academic libraries information on Twitter and the number of users included in each group. Figure 1 shows how the library information is disseminated directly from libraries and indirectly through intermediaries; nodes indicate the user groups, and ties represent the tweets that flow node i to j (ni → nj). The numbers on ties shows how many times tweets are retweeted between two nodes, and the circled numbers represent retweets within a group. This graph shows, for instance, that some library tweets are relayed 74 times from ‘Libraries’ to ‘Students’.
As was mentioned earlier, the 506 retweet users were categorized into 12 groups (Table 2). Among them, ‘University organizations’ was the largest group (15.8%). The retweet network (Figure 1) shows that the users in this group relay library messages many times and those messages are relayed again by libraries and other user groups. This result supports the finding that institutions within a university, including libraries, retweet each other's messages to promote their accounts and diffuse messages to additional university members (Mollett et al, 2011). So, users can receive library information indirectly from retweets by university organizations. This group seems to play a role in forwarding library information as well as using that information.
Table 2. Retweet User Groups
The second largest group is ‘Students’. This supports the fact that academic libraries provide Twitter services with content mainly for their students (Aharony, 2011; Loudon & Hall, 2010; Stuart, 2010). The retweet network (Figure 1) shows that students retweeted library messages from not only libraries but also other groups such as university organizations, information professionals, and other students. They appear to be intermediaries that then reach more users.
The ‘Local organizations’ (7.3%) group is in the middle range of the retweet users, but more academic library messages are transmitted through them than other groups, except for ‘University organizations’. This phenomenon indicates non-homophily accounts can play a role in diffusing academic libraries information.
Another academic library user is faculty which is included in the ‘Scholar’ group. However, the number of users in the group is small and few of their retweets are diffused again. They are the least active group in our data sample.
This study examined users who retweeted academic libraries' tweets in order to identify those tweets that were then further disseminated by 12 different groups of users. The most active user group was university organizations and the smallest and least active group was faculty. Academic libraries' tweets were directly relayed by users as well as indirectly delivered by intermediaries such as university organizations, local organizations, and information professionals.
Studies on the use of Twitter in other fields show that Twitter can be similar to word of mouth (Jansen et al., 2009). The results of this study indicate that academic libraries' Twitter use can be similar to word of mouth among various user groups including their patrons. The findings will contribute to how academic libraries can make the most of their Twitter services. Future research will focus on retweeted messages among academic libraries' tweets to discover any differences in information content among user groups.