To help users manage the overwhelming influx of smartphone notifications, this study explores how large language models (LLMs) can be leveraged to generate notification summaries. We developed an Android application that integrates ChatGPT to summarize notifications and conducted an in-the-wild deployment to examine how users guided the model. To further understand user expectations for LLM-generated summaries, we interviewed 20 participants following a week-long engagement with the app. Our findings reveal five main strategies that users employed in their prompts for generating summaries. Additionally, interviewees expected summaries to prioritize three types of notifications, preferred three levels of information disclosure influenced by content anticipation and perceived criticality, and used three different approaches to synthesizing notifications based on their interrelationships. Finally, interviewees envisioned notification summarization functioning like a virtual assistant, desiring capabilities beyond simple information condensation, including support for task and information management, revisiting archived content, and tracking activities for reflection.

The proliferation of influencers on social-media platforms has drawn considerable research attention, particularly in the field of marketing. Nevertheless, there is limited understanding among HCI and communication researchers of what leads these social-media influencers’ (SMIs’) audiences to favor and choose their content over traditional media. To fill this gap, we conducted semi-structured interviews with 45 SMI audience members. Our findings revealed a total of eight categories of SMIs’ appeals, i.e., factors that made the interviewees favor their content over traditional media. These appeals can further be grouped into three categories: content, presentation, and closeness. In particular, we identified the key role of SMIs’ perceived high autonomy and independence, which led both their content and their presentation styles to be seen as distinct from and more appealing than traditional media. Likewise, four closeness appeals made our participants feel emotionally attached to SMIs, resulting in sustained engagement.

Attention-management tools can restrict online communication, but may cause collateral damage to their users’ fulfillment of communication expectations. This paper explores the idea of integrating attention management into instant messaging (IM), by 1) disclosing restriction status via an online status indicator (OSI) to manage contacts’ expectations, and 2) imposing communication limits to reduce communication distraction. We used a speed-dating design method to allow 43 participants to rapidly compare 48 types of OSI restriction in various conversational contexts. We identified two “tug-of-wars” that take place when attention management is integrated into IM apps: one between fulfilling one’s contacts’ expectations and protecting one’s own attention, and the other, between protecting one’s privacy and asserting the justifiability of using communication restrictions. We also highlighted the participants’ desire to be diplomatic for sustaining their positive images and maintaining relational connectedness. Finally, we provide design recommendations for integrating attention management into IM apps.

We investigate instant-messaging (IM) users’ sense-making and practices around read-receipts: a feature of IM apps for supporting the awareness of turn-taking, i.e., whether a message recipient has read a message. Using a grounded-theory approach, we highlight the importance of five contextual factors – situational, relational, interactional, conversational, and personal – that shape the variety of IM users’ sense-making about read-receipts and strategies for utilizing them in different settings. This approach yields a 21-part typology comprising five types of senders’ speculation about why their messages with read-receipts have not been answered; eight types of recipients’ causes/reasons behind such non-response; and four types of senders’ and recipients’ subsequent strategies, respectively. Mismatches between senders’ speculations about un-responded-to read-receipted messages (URRMs) and recipients’ self-reported explanations are also discussed as sources of communicative friction. The findings reveal that, beyond indicating turn-taking, read-receipts have been leveraged as a strategic tool for various purposes in interpersonal relations.

BACKGROUND: Bacterial tyrosine-kinases (BY-kinases), which play an important role in numerous cellular processes, are characterized as a separate class of enzymes and share no structural similarity with their eukaryotic counterparts. However, in silico methods for predicting BY-kinases have not been developed yet. Since these enzymes are involved in key regulatory processes, and are promising targets for anti-bacterial drug design, it is desirable to develop a simple and easily interpretable predictor to gain new insights into bacterial tyrosine phosphorylation. This study proposes a novel SCMBYK method for predicting and characterizing BY-kinases. RESULTS: A dataset consisting of 797 BY-kinases and 783 non-BY-kinases was established to design the SCMBYK predictor, which achieved training and test accuracies of 97.55 and 96.73%, respectively. Furthermore, the leave-one-phylum-out method was used to predict specific bacterial phyla hosts of target sequences, gaining 97.39% average test accuracy. After analyzing SCMBYK-derived propensity scores, four characteristics of BY-kinases were determined: 1) BY-kinases tend to be composed of α-helices; 2) the amino-acid content of extracellular regions of BY-kinases is expected to be dominated by residues such as Val, Ile, Phe and Tyr; 3) BY-kinases structurally resemble nuclear proteins; 4) different domains play different roles in triggering BY-kinase activity. CONCLUSIONS: The SCMBYK predictor is an effective method for identification of possible BY-kinases. Furthermore, it can be used as a part of a novel drug repurposing method, which recognizes putative BY-kinases and matches them to approved drugs. Among other results, our analysis revealed that azathioprine could suppress the virulence of M. tuberculosis, and thus be considered as a potential antibiotic for tuberculosis treatment.