In this digital age, information users have experienced dynamic changes as they search, use, (re-)create, and disseminate information. In the users’ information environment, two changes have been recognized in the use of multimedia information and roles of information users. Due to the advanced digital information and network technologies, professionals in specialized areas are not the only users of multimedia; general public users interact with multimedia when they communicate with others. A great portion of Web searching activities is comprised of multimedia searching (ComScore 2010), and image is one of top multimedia formats in use (St. Jean et al. 2012). In addition, with the popularity of social media service, users have played multiple roles, from information consumer to information creator and information distributor, as they chat daily, converse actively, share information, and even report news through various social media services. When users dynamically use social media services for their daily lives, the information resource formats in which users engage has been shifted from text-only to also including multimedia in their digital information environment.

With the changes taking place in the information environment, it would be a worthwhile effort to gain a better understanding of the growing information phenomenon that embraces users’ new roles (as information creators and disseminators) and investigates multimedia information being used as a main source of information. This study attempts to specifically examine Twitter messages containing images. Twitter, one of the fastest growing social media applications, is a new form of communication in which people share information, assert personal opinions, request actions from the public, promote organizations’ activities, and engage in conversation. These various Twitter activities can be categorized into two main purposes: sharing information and wielding influence. These purposes create unique aspects of Twitter messages and activities. First, Twitter users share information, whether it is news, personal updates, marketing, and so on; therefore, compared to other social media services, Twitter can be characterized as an information-oriented social media service (boyd, Golder, and Lotan 2010). Second, Twitter messages - or tweets - can be retweeted by other users. When users broadcast tweets in this manner, the messages can spread to a wider audience and can potentially influence large populations and public opinions. Finally, a tweet is a short message limited to 140 characters, but users can embed images, videos, and URLs. In other words, on Twitter, multimedia information is actively used for disseminating information. Considering these features, the authors assume that Twitter offers a unique opportunity to study the dynamics of the information environment including its active information users and multimedia information.

With the purpose of understanding the characteristics of tweets, image use, and users in Twitter communication, this study examined tweets with images addressing the topic of the Boston Marathon Bombing on April 2013. By analyzing tweets, the purpose of the study is to demonstrate an understanding of how people use images when communicating with others in the context of social network services.

More specifically, the following research objectives will guide the direction of this study:

To characterize the Twitter messages containing images in terms of influential and favorited tweets. To characterize the image uses in the Twitter messages in terms of influential and favorited tweets. To characterize the users using images in terms of influential and favorited tweets. To compare the general, influential, and favorited tweets in terms of message, image use, and user.

As Twitter has gained popularity worldwide, several lines of research have been conducted in order to understand tweeting behaviors and information diffusion through Twitter. For the current study, related studies are classified into two lines of research: image use for image information needs, and Twitter use for information.

There have been substantial research endeavors to identify users’ image needs through various approaches. One of prominent approaches to users’ image needs is to analyze image requests and search queries for images. One direction of this approach is to focus on users’ image needs in terms of special collections and specific user groups such as art history, history, illustration, and news journalism (Choi and Rasmussen 2003; Armitage and Enser 1997; Chen 2001; Enser and McGregor 1992; Hastings 1995; Jörgensen and Jörgensen 2005; Westman and Oittinen 2006). The other is to understand general users’ image needs in terms of a vast range of image collections and users’ daily lives, mostly from data collected through web search logs (Goodrum and Spink 2001; Jansen 2008; Cunningham Bainbridge and Masoodian 2004; Panofsky 1955; Chung and Yoon 2011; Chung and Yoon 2009). A recent trend in understanding users’ image needs is to identify the needs in context. While there have been a wide variety of contexts for image needs, image use has been recognized as one of crucial factors to users’ image needs (McCay-Peet and Toms 2009). Fidel (1997) defined the two extreme ends of image use as object pole and data pole, Conniss, Ashford, and Graham (2000) identified seven image uses: illustration, information dissemination, information processing, learning, aesthetic, idea generation, and emotive and persuasive uses using Fidel’s two poles. A considerable amount of research has been conducted utilizing the two frameworks provided by Fidel and Conniss, Ashford, and Graham. This line of research has shown that image uses in the object pole, including aesthetic, idea generation, and emotive and persuasive uses, are not limited to everyday life image seeking (Westman and Oittinen 2006; Chung and Yoon 2011) but are also used in journalism and history fields (McCay-Peet and Toms 2009). Clearly, image use is indicated as one of the significant indicators for users’ image needs (McCay-Peet and Toms 2009; Chang and Lee 2001; Coutright 2007; Johnson 2003). Recently, as the environment for image use has changed and expanded to include social media services, understanding how users use images in the context of social media is valuable to identify users’ image needs.

Twitter can be defined as a microblogging service which allows a user to send a brief 140 character message, called a “tweet”, to others. Depending on users’ preferences, tweets can be sent to only specific users or to public users. Several functions are available such as responding with “@”, retweeting, and hashtags (#) to send information specific users and designate specific topics for their messages. As Twitter gains popularity worldwide, there have been research efforts to understand users’ behaviors and information diffusion through Twitter. Several distinctive lines of research are recognized in the line of this current research. The first line of research focuses on the characteristics of Twitter in terms of quantitative analyses such as content analysis of Twitter messages and users. The studies in this focus have demonstrated the growth of Twitter, hashtag and @ usages, geographic distributions of users and messages, message categorizations, and users’ characteristics (Java et al. 2007; Krishnamurthy and Arlitt 2008; Naaman, Boase, and Lai 2010; Westman and Freund 2010). Second, by focusing on information diffusion through retweeting behaviors, research has attempted to understand retweeting behaviors, including retweet practices, the characteristics of retweeted messages, the reasons for retweeting, editing behaviors during the retweeting procedure, affecting factors on retweeting, and usage patterns of the @ symbol in Twitter (boyd, Golder, and Lotan 2010; Honeycutt and Herring 2009; Mustafaraj and Metaxas 2011; Nagarajan, Purohit, and Sheth 2010; Suh et al. 2010; Yang et al. 2010). Another line of research in Twitter is related to visualization of Twitter network in terms of users and messages (Bruns 2012; Lerman and Ghosh 2010). Finally, there have been endeavors to identify Twitter behaviors among specific user groups such as police user groups (Crump 2011), Congress member user groups in the U.S. (Golbeck, Grimes, and Rogers 2010), and local government user groups in the U.K. (Panagiotopoulos and Sams 2012). These lines of research attempted to understand users’ behaviors and characteristics of information diffusion through Twitter. However, although image use in the context of social media is highly relevant information for identifying users’ image needs, image use within tweets has had little examination.

In order to understand image use in the context of tweets, the messages containing images were collected for data analysis. Most of images in the Twitter messages have URLs starting with “pic.twitter.com”, so the messages were retrieved from the Twitter website (www.twitter.com) with the keywords “pic.twitter.com” AND “Boston” during the period between April 15 and April 30, 2013 for collecting the data set. By default, the Twitter website provides an option of ‘Top’ or ‘All’ tweets and tweets with ‘Top’ option were selected. For this study, the total number of collected tweets was 1,589. To characterize and compare the features of message, image use, and user among influential Twitter messages (i.e., highly retweeted messages), favorited Twitter messages (i.e., highly favorited messages by users), and general Twitter messages (i.e., random Twitter messages), three sets were selected from 1,589 tweets.

(1) influential Twitter message data set: the top 200 most retweeted messages were selected and 192 messages were used for analysis since there were deleted images and accounts. (2) favorited Twitter message data set: the top 200 favorited messages were selected and 189 messages were used for analysis since there were deleted images and accounts. (3) general Twitter message data set1): 200 messages were randomly selected and 174 messages were used for analysis since there were deleted images and accounts.

In order to identify the characteristics of tweet, image use, and user, two phases of analysis were conducted. In the first phase, categorical analyses were performed for messages, image uses, and users for the data sets of this study. In this phase, coding schemes were adopted and modified from previous studies. For types of tweets, the coding scheme developed in Yoon and Chung (2013) was adopted. In Yoon and Chung (2013)’s study, initial categories were synthesized from previous studies; categories of Twitter messages were summarized from several previous studies (Honeycutt and Herring 2009; Java et al. 2007; Naaman, Boase, and Lai 2010; Westman and Freund 2010) and eight types of messages were recognized as shown in Table 1.