The effects of Facebook on academic performance have attracted both public and scholarly attention. Prior research found that Facebook use is linked to poor academic performance, suggesting that Facebook distracts students from studying. These studies, which are primarily based on survey responses, are insufficient to uncover exactly how Facebook is used or embedded in students' studying activities. To capture unbiased, detailed use patterns and to investigate the context of Facebook use, we studied 50 college students using automatic logging and experience sampling. We analyzed the activities and attentional states of students prior to visiting Facebook. Results show that GPAs of frequent Facebook users do not suffer. Students with high GPAs spend shorter time in each Facebook session and shorter Facebook use often follows schoolwork. These results point to a possibility that potentially problematic Facebook use occurs when students are in a spree of leisure activities, not while studying.

College students are exposed to a vast amount of information on political and social issues through social media. We studied how college students engage with political and social issues on Facebook in a weeklong study with 50 participants using diary entries and interviews. The interviews revealed a duality of benefits for using Facebook for news and they also revealed challenges of self-presentation around news. Benefits included gaining multiple perspectives and enabling social sense making, providing personal relevance and convenience of access, and the opportunity for social engagement. Impression management and disclosure concerns strongly influence some people to refrain from commenting or sharing news. We discuss the challenges that context collapse poses for Facebook news readers. We suggest design ideas and future directions to encourage more balanced participation with news among college students.

The amount of sleep college students receive has become a pressing societal concern. While studies show that information technology (IT) use affects sleep, here we examine the converse: how sleep duration might affect IT use. We conducted an in situ study, and logged computer and phone use and collected sleep diaries and daily surveys of 76 college students for seven days, all waking hours. We examined effects of sleep duration and sleep debt. Our results show that with less sleep, people report higher perceived work pressure and productivity. Also, computer focus duration is significantly shorter suggesting higher multitasking. The more sleep debt, the more Facebook use and the higher the negative mood. With less sleep, people may seek out activities requiring less attentional resources such as social media use. Our results have theoretical implications for multitasking: physiological and cognitive reasons could explain more computer activity switches: related to less sleep.

We take an ecological approach to studying social media use and its relation to mood among college students. We conducted a mixed-methods study of computer and phone logging with daily surveys and interviews to track college students' use of social media during all waking hours over seven days. Continual and infrequent checkers show different preferences of social media sites. Age differences also were found. Lower classmen tend to be heavier users and to primarily use Facebook, while upper classmen use social media less frequently and utilize sites other than Facebook more often. Factor analysis reveals that social media use clusters into patterns of content-sharing, text-based entertainment/discussion, relationships, and video consumption. The more constantly one checks social media daily, the less positive is one's mood. Our results suggest that students construct their own patterns of social media usage to meet their changing needs in their environment. The findings can inform further investigation into social media use as a benefit and/or distraction for students.

While HCI has focused on multitasking with information workers, we report on multitasking among Millennials who grew up with digital media - focusing on college students. We logged computer activity and used biosensors to measure stress of 48 students for 7 days for all waking hours, in their in situ environments. We found a significant positive relationship with stress and daily time spent on computers. Stress is positively associated with the amount of multitasking. Conversely, stress is negatively associated with Facebook and social media use. Heavy multitaskers use significantly more social media and report lower positive affect than light multitaskers. Night habits affect multitasking the following day: late-nighters show longer duration of computer use and those ending their activities earlier in the day multitask less. Our study shows that college students multitask at double the frequency compared to studies of information workers. These results can inform designs for stress management of college students.

For information workers who monitor numerous constantly updating data streams, conserving cognitive resources is crucial. This study evaluated how an interface affects information workers' ability to grasp critical information from multiple text-based chat streams under time pressure. We designed and built a working prototype that displays ten chat streams simultaneously in standard chat windows (ST) and ticker tapes (TT). We conducted a lab experiment to evaluate differences in how these two interfaces support signal and context detection. We found that with ST, participants detected significantly more target words (SAT words) with rarer frequency and significantly more context information (disaster facts) than with TT. Our results show that while TT is potentially better for overview scanning of multiple streams, ST is likely to be better for multi-tasking. Our study informs the design of future multi-chat systems so that large amounts of information can be easier to detect and process.

Since 2006 social media use has grown dramatically in China. Social media has become a stage for citizens to report and disseminate news and to vocalize viewpoints, at times competing with reports from highly curated official media sources. These competing news channels, oftentimes presenting contradictory information, raise questions about citizens' trust in these different media. This study explores the level of trust Chinese Internet users place on news from social media versus official media. We conducted a large-scale anonymous survey in China that revealed that official and citizen news attract different audience groups and each group uses different features to assess news trustworthiness. We present a model for predicting preference for news from citizen media. The results reveal features of social media that explain why some citizens trust it as a channel for news. The results also suggest that in highly regulated news environments, citizen media has the potential to become an alternative news channel where citizens can trust each other for information.

Assigning keywords to articles can be extremely costly. In this paper we propose a new approach to biomedical concept extraction using semantic features of concept graphs to help in automatic labeling of scientific publications. The proposed system extracts key concepts similar to author-provided keywords. We represent full-text documents by graphs and map biomedical terms to predefined ontology concepts. In addition to occurrence frequency weights, we use concept relation weights to rank potential key concepts. We compare our technique to that of KEA's, a state-of-the-art keyphrase extraction software. The results show that using the relations weight significantly improves the performance of concept extraction. The results also highlight the subjectivity of the concept extraction procedure as well as of its evaluation.