It is typically expected that when people work together, they can often accomplish goals that are difficult or even impossible for individuals. We consider this notion of the group achieving more than the sum of all individuals' achievements to be the synergic effect in collaboration. Similar expectation exists for people working in collaboration for information seeking tasks. We, however, lack a methodology and appropriate evaluation metrics for studying and measuring the synergic effect. In this paper we demonstrate how to evaluate this effect and discuss what it means to various collaborative information seeking (CIS) situations. We present a user study with four different conditions: single user, pair of users at the same computer, pair of users at different computers and co-located, and pair of users remotely located. Each of these individuals or pairs was given the same task of information seeking and usage for the same amount of time. We then combined the outputs of single independent users to form artificial pairs, and compared against the real pairs. Not surprisingly, participants using different computers (co-located or remotely located) were able to cover more information sources than those using a single computer (single user or a pair). But more interestingly, we found that real pairs with their own computers (co-located or remotely located) were able to cover more unique and useful information than that of the artificially created pairs. This indicates that those working in collaboration achieved something greater and better than what could be achieved by adding independent users, thus, demonstrating the synergic effect. Remotely located real teams were also able to formulate a wider range of queries than those pairs that were colocated or artificially created. This shows that the collaborators working remotely were able to achieve synergy while still being able to think and work independently. Through the experiments and measurements presented here, we have also contributed a unique methodology and an evaluation metric for CIS.

Many theories and models exist for understanding and explaining information seeking processes (ISP) for individuals. Such is not the case for collaborative information seeking (CIS), despite its growing importance. In this paper we take Kuhlthau's ISP model, designed for individual information seeking, and map it to a CIS situation. We present a laboratory study with 84 participants in 42 pairs and demonstrate how their information seeking processes over two sessions can be mapped to various stages of the ISP model. In addition, we explore the affective dimension of information seeking as well as perceived relevance expressed by the participants through their interactions. We discuss similarities and disparities of ISP for individuals and collaborative information seeking. In particular, we show that there is a logical progression from uncertainty about the task to being satisfied about the collected information among the participants; and at the same time, there is a lack of clear segmentation between stages of formulating information need, exploring information, and collecting it. The latter can be attributed to exploratory search tasks and interactions among the collaborators.

Facial expressions constitute a rich source of non-verbal cues in face-to-face communication. They provide interlocutors with resources to express and interpret verbal messages, which may affect their cognitive and emotional processing. Contrarily, computer-mediated communication (CMC), particularly text-based communication, is limited to the use of symbols to convey a message, where facial expressions cannot be transmitted naturally. In this scenario, people use emoticons as paralinguistic cues to convey emotional meaning. Research has shown that emoticons contribute to a greater social presence as a result of the enrichment of text-based communication channels. Additionally, emoticons constitute a valuable resource for language comprehension by providing expressivity to text messages. The latter findings have been supported by studies in neuroscience showing that particular brain regions involved in emotional processing are also activated when people are exposed to emoticons. To reach an integrated understanding of the influence of emoticons in human communication on both socio-cognitive and neural levels, we review the literature on emoticons in three different areas. First, we present relevant literature on emoticons in CMC. Second, we study the influence of emoticons in language comprehension. Finally, we show the incipient research in neuroscience on this topic. This mini review reveals that, while there are plenty of studies on the influence of emoticons in communication from a social psychology perspective, little is known about the neurocognitive basis of the effects of emoticons on communication dynamics.

With the rapid development of social media, spontaneously user‐generated content such as tweets and forum posts have become important materials for tracking people's opinions and sentiments online. A major hurdle for current state‐of‐the‐art automatic methods for sentiment analysis is the fact that human communication often involves the use of sarcasm or irony, where the author means the opposite of what she/he says. Sarcasm transforms the polarity of an apparently positive or negative utterance into its opposite. Lack of naturally occurring utterances labeled for sarcasm is one of the key problems for the development of machine‐learning methods for sarcasm detection. We report on a method for constructing a corpus of sarcastic Twitter messages in which determination of the sarcasm of each message has been made by its author. We use this reliable corpus to compare sarcastic utterances in Twitter to utterances that express positive or negative attitudes without sarcasm. We investigate the impact of lexical and pragmatic factors on machine‐learning effectiveness for identifying sarcastic utterances and we compare the performance of machine‐learning techniques and human judges on this task.

In this demo we introduce Coagmento, a tool for supporting interactive information seeking process of teams in various collaborative scenarios. Coagmento has been used in several laboratory and field studies to understand issues related to collaborative information seeking (CIS) and deriving lessons and guidelines for providing suitable support for people working in collaboration for information-intensive projects. From its initial design, Coagmento has evolved through the introduction of new features and the support for both web-based as well as mobile systems. Using appropriate research methodologies, Coagmento has proven to be a useful tool for collecting behavioral data of users enabling researchers to better understand different dimensions of the collaborative process of teams as well as single users while searching information online. KeywordsCollaborative search, interactive search, CSCW.