新聞推播通知已逐漸成為一重要獲取新聞的管道，但使用者並非隨時總是有充足的時間與認知資源來閱讀推播新聞通知。然而，人們在不同新聞推播時機，會以甚麼閱讀模式與其閱讀表現如何尚未有太多相關研究。我們開發了一款多元新聞入口的新聞app — NewsMoment，提供來自九家新聞媒體真實的新聞通知與新聞內容，並且透過app收集使用者的新聞閱讀行為。分析經驗抽樣問卷(ESM)實驗結果發現，使用者常以兩種淺閱讀模式(shallow reading) —掃視與未投入—閱讀推播的新聞通知。這兩種淺閱讀看似相近，但在分布比例、觸發因素、合適時機以及自我衡量的閱讀投入程度與新聞可信程度均有所不同。我們也發現合適閱讀新聞時機與接收通知時機、查看通知時機有所不同。我們依此提出設計新聞推播機制的建議，預期能降低淺閱讀出現的機率。

Pushed notifications from mobile news apps are an important means of access to news, but people do not always have sufficient time or cognitive resources to process them. Nevertheless, whether and to what extent news-reading behavior and performance are associated with particular moments of pushed-news delivery are understudied. We therefore built NewsMoment, a smartphone news-aggregation app that logs its users’ reading behavior and sends pushed news notifications for real news items from up to nine news organizations. Our ESM study found that pushed news was associated with two shallow reading modes – Scanning and Unengaged – which, though seemingly similar, were distinct in their prevalence, triggers, opportune moments, and self-assessed reading engagement and news items’ perceived credibility. We also found that opportune moments for reading entire articles were distinct from those for receiving notifications and checking news titles. These findings inform our pushed-news design recommendations aimed at reducing shallow reading.

摘要 i
ABSTRACT ii
致謝 iii
Table of Contents iv
List of Tables vii
List of Figures vii
CHAPTER 1 INTRODUCTION 1
CHAPTER 2 RELATED WORK 5
2.1 Mobile News Consumption 5
2.2 News Reading Behavior 7
2.3 Opportune Moments for Delivering Content 9
CHAPTER 3 METHODOLOGY 12
3.1 NewsMoment 12
3.1.1 Core Features and User Interface 13
3.1.2 Pushed News Notifications 14
3.1.3 Data Collection 15
3.2 ESM Study 16
3.2.1 ESM Mechanism 16
3.2.2 ESM Questionnaire 18
3.3 Study Procedure 23
3.4 Recruitment and Participants 24
3.5 Data Cleaning and Analysis 25
CHAPTER 4 RESULTS 28
4.1 Mobile News Behavior 28
4.1.1 Overall Mobile News Behavior 28
4.1.2 Four Distinct News Reading Patterns 28
4.1.3 Identifying Reading Modes on NewsMoment Using Clustering 30
4.1.4 Comparison of the Four Reading Modes 31
4.1.5 Initiation of News Reading: News App vs. Pushed News 34
4.1.6 Choice of Reading Mode by News Category 35
4.2 Influence of Moments on Pushed News Reading 37
4.2.1 Influence of Perceived Opportuneness of the Moment 38
4.2.2 Self-reported Interest, Purpose, and Influential Factors in News Reading at (In) Opportune Moments 40
4.2.3 Reading Modes across Activity Contexts 43
4.3 Self-Assessed Reading Engagement, Comprehension, and Perceived Credibility of Pushed News 47
4.3.1 Self-Assessed Reading Coverage, Engagement, and Comprehension of Pushed News 48
4.3.2 Perceived Credibility of Pushed News 49
CHAPTER 5 DISCUSSION 52
5.1 The Two Distinct Shallow Reading Modes: Unengaged and Scanning 52
5.2 Opportune Moment for Pushed News Delivery on Smartphones 55
5.3 Implications for Pushing News on Smartphones 56
CHAPTER 6 CONCLUSION 59
6.1 Research Limitation 59
6.2 Conclusion 60
REFERENCE 62
APPENDIX 75

1. Adamczyk, P. D., & Bailey, B. P. (2004). If not now, when? The effects of interruption at different moments within task execution. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 271–278. https://doi.org/10.1145/985692.985727
2. Al-Saggaf, Y., & O’Donnell, S. B. (2019). Phubbing: Perceptions, reasons behind, predictors, and impacts. Human Behavior and Emerging Technologies, 1(2), 132–140. https://doi.org/10.1002/hbe2.137
3. Appelman, A., & Sundar, S. S. (2016). Measuring Message Credibility: Construction and Validation of an Exclusive Scale. Journalism & Mass Communication Quarterly, 93(1), 59–79. https://doi.org/10.1177/1077699015606057
4. Boase, J., & Ling, R. (2013). Measuring Mobile Phone Use: Self-Report Versus Log Data. Journal of Computer-Mediated Communication, 18(4), 508–519. https://doi.org/10.1111/jcc4.12021
5. Caronia, L. (2005). Feature Report: Mobile Culture: An Ethnography of Cellular Phone Uses in Teenagers’ Everyday Life. Convergence, 11(3), 96–103. https://doi.org/10.1177/135485650501100307
6. Carreira, R., Crato, J. M., Gon?alves, D., & Jorge, J. A. (2004). Evaluating adaptive user profiles for news classification. Proceedings of the 9th International Conference on Intelligent User Interface - IUI ’04, 206. https://doi.org/10.1145/964442.964481
7. Chan, M. (2015). Examining the influences of news use patterns, motivations, and age cohort on mobile news use: The case of Hong Kong. Mobile Media & Communication, 3(2), 179–195. https://doi.org/10.1177/2050157914550663
8. Chang, Y.-J., Chung, Y.-J., & Shih, Y.-H. (2019). I Think It’s Her: Investigating Smartphone Users’ Speculation about Phone Notifications and Its Influence on Attendance. Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, 1–13. https://doi.org/10.1145/3338286.3340125
9. Chang, Y.-J., & Tang, J. C. (2015). Investigating Mobile Users’ Ringer Mode Usage and Attentiveness and Responsiveness to Communication. Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services, 6–15. https://doi.org/10.1145/2785830.2785852
10. Cheng, J., Teevan, J., Iqbal, S. T., & Bernstein, M. S. (2015). Break It Down: A Comparison of Macro- and Microtasks. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 4061–4064. https://doi.org/10.1145/2702123.2702146
11. Chiang, C.-E., Chen, Y.-C., Lin, F.-Y., Feng, F., Wu, H.-A., Lee, H.-P., Yang, C.-H., & Chang, Y.-J. (2021). “I Got Some Free Time”: Investigating Task-execution and Task-effort Metrics in Mobile Crowdsourcing Tasks. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, 1–14. https://doi.org/10.1145/3411764.3445477
12. Constantinides, M., & Dowell, J. (2018). A Framework for Interaction-driven User Modeling of Mobile News Reading Behaviour. Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization, 33–41. https://doi.org/10.1145/3209219.3209229
Constantinides, M., Dowell, J., Johnson, D., & Malacria, S. (2015). Exploring mobile news reading interactions for news app personalisation. Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services, 457–462. https://doi.org/10.1145/2785830.2785860
13. Costera Meijer, I., & Groot Kormelink, T. (2015). Checking, Sharing, Clicking and Linking: Changing patterns of news use between 2004 and 2014. Digital Journalism, 3(5), 664–679. https://doi.org/10.1080/21670811.2014.937149
14. Czerwinski, M., Cutrell, E., & Horvitz, E. (2000). Instant Messaging and Interruption: Influence of Task Type on Performance.
15. Dimmick, J., Feaster, J. C., & Hoplamazian, G. J. (2011). News in the interstices: The niches of mobile media in space and time. New Media & Society, 13(1), 23–39. https://doi.org/10.1177/1461444810363452
16. Dingler, T., & Pielot, M. (2015). I’ll be there for you: Quantifying Attentiveness towards Mobile Messaging. Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services, 1–5. https://doi.org/10.1145/2785830.2785840
17. Dingler, T., Tag, B., Lehrer, S., & Schmidt, A. (2018). Reading Scheduler: Proactive Recommendations to Help Users Cope with Their Daily Reading Volume. Proceedings of the 17th International Conference on Mobile and Ubiquitous Multimedia, 239–244. https://doi.org/10.1145/3282894.3282917
18. Dingler, T., Weber, D., Pielot, M., Cooper, J., Chang, C.-C., & Henze, N. (2017). Language learning on-the-go: Opportune moments and design of mobile microlearning sessions. Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services, 1–12. https://doi.org/10.1145/3098279.3098565
19. Duffy, A., Tandoc, E., & Ling, R. (2020). Too good to be true, too good not to share: The social utility of fake news. Information, Communication & Society, 23(13), 1965–1979. https://doi.org/10.1080/1369118X.2019.1623904
20. Esiyok, C., Kille, B., Jain, B.-J., Hopfgartner, F., & Albayrak, S. (2014). Users’ reading habits in online news portals. Proceedings of the 5th Information Interaction in Context Symposium, 263–266. https://doi.org/10.1145/2637002.2637038
21. Fidalgo, A. (2009). Pushed news: When the news comes to the cellphone. Brazilian Journalism Research, 5(2), 113–124. https://doi.org/10.25200/BJR.v5n2.2009.214
22. Fischer, J. E., Greenhalgh, C., & Benford, S. (2011). Investigating episodes of mobile phone activity as indicators of opportune moments to deliver notifications. Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services, 181–190. https://doi.org/10.1145/2037373.2037402
23. Fischer, J. E., Yee, N., Bellotti, V., Good, N., Benford, S., & Greenhalgh, C. (2010). Effects of content and time of delivery on receptivity to mobile interruptions. Proceedings of the 12th International Conference on Human Computer Interaction with Mobile Devices and Services, 103–112. https://doi.org/10.1145/1851600.1851620
24. Grinberg, N. (2018). Identifying Modes of User Engagement with Online News and Their Relationship to Information Gain in Text. Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW ’18, 1745–1754. https://doi.org/10.1145/3178876.3186180
25. Gu, Y. H., Yoo, S. J., Piao, Z., No, J., Jiang, Z., & Yin, H. (2016). A smart-device news recommendation technology based on the user click behavior. Proceedings of the Sixth International Conference on Emerging Databases: Technologies, Applications, and Theory, 9–16. https://doi.org/10.1145/3007818.3007821
26. Ho, B.-J., Balaji, B., Koseoglu, M., Sandha, S., Pei, S., & Srivastava, M. (2020). Quick Question: Interrupting Users for Microtasks with Reinforcement Learning. ArXiv:2007.09515 [Cs]. http://arxiv.org/abs/2007.09515
27. Ho, J., & Intille, S. S. (2005). Using context-aware computing to reduce the perceived burden of interruptions from mobile devices. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 909–918. https://doi.org/10.1145/1054972.1055100
28. Homma, R., Seki, Y., Yoshida, M., & Umemura, K. (2020). Analysis of Short Dwell Time in Relation to User Interest in a News Application. ArXiv:2012.13992 [Cs]. http://arxiv.org/abs/2012.13992
29. Hudson, S., Fogarty, J., Atkeson, C., Avrahami, D., Forlizzi, J., Kiesler, S., Lee, J., & Yang, J. (2003). Predicting human interruptibility with sensors: A Wizard of Oz feasibility study. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 257–264. https://doi.org/10.1145/642611.642657
30. Iqbal, S., & Horvitz, E. (2010). Notifications and Awareness: A Field Study of Alert Usage and Preferences. https://www.microsoft.com/en-us/research/publication/notifications-and-awareness-a-field-study-of-alert-usage-and-preferences/
31. Iqbal, S. T., & Bailey, B. P. (2007). Understanding and developing models for detecting and differentiating breakpoints during interactive tasks. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 697–706). Association for Computing Machinery. https://doi.org/10.1145/1240624.1240732
32. Iqbal, S. T., & Bailey, B. P. (2008). Effects of intelligent notification management on users and their tasks. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 93–102. https://doi.org/10.1145/1357054.1357070
33. Jeong, S.-H., & Hwang, Y. (2012). Does Multitasking Increase or Decrease Persuasion? Effects of Multitasking on Comprehension and Counterarguing. Journal of Communication, 62(4), 571–587. https://doi.org/10.1111/j.1460-2466.2012.01659.x
34. Kang, H., Lee, J. K., You, K. H., & Lee, S. (2013). Does Online News Reading and Sharing Shape Perceptions of the Internet as a Place for Public Deliberations? Mass Communication and Society, 16(4), 533–556. https://doi.org/10.1080/15205436.2012.746711
35. Kirchner, J., & Reuter, C. (2020). Countering Fake News: A Comparison of Possible Solutions Regarding User Acceptance and Effectiveness. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW2), 140:1-140:27. https://doi.org/10.1145/3415211
36. Kobayashi, T., & Boase, J. (2012). No Such Effect? The Implications of Measurement Error in Self-Report Measures of Mobile Communication Use. Communication Methods and Measures, 6(2), 126–143. https://doi.org/10.1080/19312458.2012.679243
37. Kodinariya, T., & Makwana, P. (2013). Review on Determining of Cluster in K-means Clustering. International Journal of Advance Research in Computer Science and Management Studies, 1, 90–95.
38. Lagun, D., Hsieh, C.-H., Webster, D., & Navalpakkam, V. (2014). Towards better measurement of attention and satisfaction in mobile search. Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval, 113–122. https://doi.org/10.1145/2600428.2609631
39. Lagun, D., & Lalmas, M. (2016). Understanding User Attention and Engagement in Online News Reading. Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, 113–122. https://doi.org/10.1145/2835776.2835833
40. Lang, A. (2000). The Limited Capacity Model of Mediated Message Processing. Journal of Communication, 50(1), 46–70. https://doi.org/10.1111/j.1460-2466.2000.tb02833.x
41. Lathia, N., Pejovic, V., Rachuri, K. K., Mascolo, C., Musolesi, M., & Rentfrow, P. J. (2013). Smartphones for Large-Scale Behavior Change Interventions. IEEE Pervasive Computing, 12(3), 66–73. https://doi.org/10.1109/MPRV.2013.56
42. Lee, H.-P., Chen, K.-Y., Lin, C.-H., Chen, C.-Y., Chung, Y.-L., Chang, Y.-J., & Sun, C.-R. (2019). Does Who Matter? Studying the Impact of Relationship Characteristics on Receptivity to Mobile IM Messages. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 1–12. https://doi.org/10.1145/3290605.3300756
43. Lehman-Wilzig, S. N., & Seletzky, M. (2010). Hard news, soft news, ‘general’ news: The necessity and utility of an intermediate classification. Journalism, 11(1), 37–56. https://doi.org/10.1177/1464884909350642
44. Lentferink, A., Noordzij, M. L., Burgler, A., Klaassen, R., Derks, Y., Oldenhuis, H., Velthuijsen, H., & van Gemert-Pijnen, L. (2021). On the receptivity of employees to just-in-time self-tracking and eCoaching for stress management: A mixed-methods approach. Behaviour & Information Technology, 1–27. https://doi.org/10.1080/0144929X.2021.1876764
45. Leuppert, R., & Geber, S. (2020). Commonly done but not socially accepted? Phubbing and social norms in dyadic and small group settings. Communication Research Reports, 37(3), 55–64. https://doi.org/10.1080/08824096.2020.1756767
46. Li, J., Song, J., Huang, Y., Wang, Y., & Zhang, J. (2021). Effects of different interaction modes on fatigue and reading effectiveness with mobile phones. International Journal of Industrial Ergonomics, 85, 103189. https://doi.org/10.1016/j.ergon.2021.103189
47. Lim, S., & Shim, H. (2016). Who Multitasks on Smartphones? Smartphone Multitaskers’ Motivations and Personality Traits. Cyberpsychology, Behavior, and Social Networking, 19(3), 223–227. https://doi.org/10.1089/cyber.2015.0225
48. Lu, H., Zhang, M., Ma, W., Wang, C., xia, F., Liu, Y., Lin, L., & Ma, S. (2019). Effects of User Negative Experience in Mobile News Streaming. Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 705–714. https://doi.org/10.1145/3331184.3331247
49. Luthans, F., Zhu, W., & Avolio, B. J. (2006). The impact of efficacy on work attitudes across cultures. Journal of World Business, 41(2), 121–132. https://doi.org/10.1016/j.jwb.2005.09.003
50. Mark, G., Iqbal, S., Czerwinski, M., & Johns, P. (2015). Focused, Aroused, but so Distractible: Temporal Perspectives on Multitasking and Communications. Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing, 903–916. https://doi.org/10.1145/2675133.2675221
51. Mark, G., Iqbal, S. T., Czerwinski, M., & Johns, P. (2014). Bored mondays and focused afternoons: The rhythm of attention and online activity in the workplace. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 3025–3034. https://doi.org/10.1145/2556288.2557204
52. Marshall, C. C. (2007). The gray lady gets a new dress: A field study of the times news reader. Proceedings of the 7th ACM/IEEE-CS Joint Conference on Digital Libraries, 259–268. https://doi.org/10.1145/1255175.1255226
53. McFarlane, D. C. (1999, August). Coordinating the interruption of people in human-computer interaction. In Interact (Vol. 99, No. 1999, p. 295).
54. Mehrotra, A., Hendley, R., & Musolesi, M. (2016). PrefMiner: Mining user’s preferences for intelligent mobile notification management. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 1223–1234. https://doi.org/10.1145/2971648.2971747
55. Mehrotra, A., Musolesi, M., Hendley, R., & Pejovic, V. (2015). Designing content-driven intelligent notification mechanisms for mobile applications. Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 813–824. https://doi.org/10.1145/2750858.2807544
56. Mehrotra, A., Pejovic, V., Vermeulen, J., Hendley, R., & Musolesi, M.(2016). My Phone and Me: Understanding People’s Receptivity to Mobile Notifications. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, 1021–1032. https://doi.org/10.1145/2858036.2858566
57. Morris, M. R., Counts, S., Roseway, A., Hoff, A., & Schwarz, J. (2012). Tweeting is believing? Understanding microblog credibility perceptions. Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work, 441–450. https://doi.org/10.1145/2145204.2145274
58. Moser, C., Schoenebeck, S. Y., & Reinecke, K. (2016). Technology at the Table: Attitudes about Mobile Phone Use at Mealtimes. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, 1881–1892. https://doi.org/10.1145/2858036.2858357
59. Nam, S., Bylinskii, Z., Tensmeyer, C., Wigington, C., Jain, R., & Sun, T. (2020). Using Behavioral Interactions from a Mobile Device to Classify the Reader’s Prior Familiarity and Goal Conditions. ArXiv:2004.12016 [Cs]. http://arxiv.org/abs/2004.12016
60. Nelson, J. L. (2020). The Persistence of the Popular in Mobile News Consumption. Digital Journalism, 8(1), 87–102. https://doi.org/10.1080/21670811.2019.1612766
61. Newman, N. (n.d.-a). News Alerts and the Battle for the Lockscreen. 36.
62. Newman, N. (n.d.-b). Reuters Institute Digital News Report 2020. 112.
66. O’Brien, H. L., Freund, L., & Kopak, R. (2016). Investigating the Role of User Engagement in Digital Reading Environments. Proceedings of the 2016 ACM on Conference on Human Information Interaction and Retrieval, 71–80. https://doi.org/10.1145/2854946.2854973
64. O’Conaill, B., & Frohlich, D. (1995). Timespace in the workplace: Dealing with interruptions. Conference Companion on Human Factors in Computing Systems - CHI ’95, 262–263. https://doi.org/10.1145/223355.223665
65. O’Connor, C., & Joffe, H. (2020). Intercoder Reliability in Qualitative Research: Debates and Practical Guidelines. International Journal of Qualitative Methods, 19, 1609406919899220. https://doi.org/10.1177/1609406919899220
66. Oeldorf-Hirsch, A. (2018). The Role of Engagement in Learning From Active and Incidental News Exposure on Social Media. Mass Communication and Society, 21(2), 225–247. https://doi.org/10.1080/15205436.2017.1384022
67. Okoshi, T., Nozaki, H., Nakazawa, J., Tokuda, H., Ramos, J., & Dey, A. K. (2016). Towards attention-aware adaptive notification on smart phones. Pervasive and Mobile Computing, C(26), 17–34. https://doi.org/10.1016/j.pmcj.2015.10.004
68. Okoshi, T., Ramos, J., Nozaki, H., Nakazawa, J., Dey, A. K., & Tokuda, H. (2015). Reducing users’ perceived mental effort due to interruptive notifications in multi-device mobile environments. Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing - UbiComp ’15, 475–486. https://doi.org/10.1145/2750858.2807517
69. Okoshi, T., Tsubouchi, K., Taji, M., Ichikawa, T., & Tokuda, H. (2017). Attention and engagement-awareness in the wild: A large-scale study with adaptive notifications. 2017 IEEE International Conference on Pervasive Computing and Communications (PerCom), 100–110. https://doi.org/10.1109/PERCOM.2017.7917856
70. Okoshi, T., Tsubouchi, K., & Tokuda, H. (2018). Real-world large-scale study on adaptive notification scheduling on smartphones. Pervasive and Mobile Computing, 50, 1–24. https://doi.org/10.1016/j.pmcj.2018.07.005
71. Okoshi, T., Tsubouchi, K., & Tokuda, H. (2019). Real-World Product Deployment of Adaptive Push Notification Scheduling on Smartphones. Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2792–2800. https://doi.org/10.1145/3292500.3330732
72. Park, C., Lim, J., Kim, J., Lee, S.-J., & Lee, D. (2017). Don’t Bother Me. I’m Socializing! A Breakpoint-Based Smartphone Notification System. Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, 541–554. https://doi.org/10.1145/2998181.2998189
73. Pejovic, V., Musolesi, M., & Mehrotra, A. (2015). Investigating The Role of Task Engagement in Mobile Interruptibility. Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct, 1100–1105. https://doi.org/10.1145/2786567.2794336
74. Pielot, M., Cardoso, B., Katevas, K., Serrà, J., Matic, A., & Oliver, N. (2017). Beyond Interruptibility: Predicting Opportune Moments to Engage Mobile Phone Users. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 1(3), 91:1-91:25. https://doi.org/10.1145/3130956
75. Poppinga, B., Heuten, W., & Boll, S. (2014). Sensor-Based Identification of Opportune Moments for Triggering Notifications. IEEE Pervasive Computing, 13(1), 22–29. https://doi.org/10.1109/MPRV.2014.15
76. Purcell, K., Rainie, L., Mitchell, A., & Rosenstiel, T. (2010, March 1). Understanding the Participatory News Consumer. Pew Research Center: Internet, Science & Tech. https://www.pewresearch.org/internet/2010/03/01/understanding-the-participatory-news-consumer/
77. Ratcliff, J. W., & Metzener, D. E. (1988). Pattern-matching-the gestalt approach. Dr Dobbs
Journal, 13(7), 46.
78. Sano, A., Johns, P., & Czerwinski, M. (2017). Designing opportune stress intervention delivery timing using multi-modal data. 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII), 346–353. https://doi.org/10.1109/ACII.2017.8273623
79. Sarker, H., Sharmin, M., Ali, A. A., Rahman, Md. M., Bari, R., Hossain, S. M., & Kumar, S. (2014). Assessing the availability of users to engage in just-in-time intervention in the natural environment. Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 909–920. https://doi.org/10.1145/2632048.2636082
80. Shim, H., You, K. H., Lee, J. K., & Go, E. (2015). Why do people access news with mobile devices? Exploring the role of suitability perception and motives on mobile news use. Telematics and Informatics, 32(1), 108–117. https://doi.org/10.1016/j.tele.2014.05.002
81. Stroud, N. J., Peacock, C., & Curry, A. L. (2020). The Effects of Mobile Push Notifications on News Consumption and Learning. Digital Journalism, 8(1), 32–48. https://doi.org/10.1080/21670811.2019.1655462
82. Tanaka, T., & Fujita, K. (2011). Study of user interruptibility estimation based on focused application switching. Proceedings of the ACM 2011 Conference on Computer Supported Cooperative Work, 721–724. https://doi.org/10.1145/1958824.1958954
83. Thorndike, R. L. (1953). Who belongs in the family. Psychometrika, 267–276.
84. Toch, E., Chassidim, H., & Hatuka, T. (2020). Can you Turn it Off?: The Spatial and Social Context of Mobile Disturbance. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW2), 1–18. https://doi.org/10.1145/3415162
85. Trafton, J. G., Altmann, E. M., Brock, D. P., & Mintz, F. E. (2003). Preparing to resume an interrupted task: Effects of prospective goal encoding and retrospective rehearsal. International Journal of Human-Computer Studies, 58(5), 583–603. https://doi.org/10.1016/S1071-5819(03)00023-5
86. Turner, L. D., Allen, S. M., & Whitaker, R. M. (2017). Reachable but not receptive. Pervasive and Mobile Computing, 40(C), 480–494. https://doi.org/10.1016/j.pmcj.2017.01.011
87. Turner, L. D., Allen, S. M., & Whitaker, R. M. (2015). Push or Delay? Decomposing Smartphone Notification Response Behaviour. In A. A. Salah, B. J. A. Kröse, & D. J. Cook (Eds.), Human Behavior Understanding (pp. 69–83). Springer International Publishing. https://doi.org/10.1007/978-3-319-24195-1_6
88. Use of mobile devices for news continues to grow, outpacing desktops and laptops. (2018, July 17). Benton Foundation. https://www.benton.org/headlines/use-mobile-devices-news-continues-grow-outpacing-desktops-and-laptops
89. van Berkel, N., Ferreira, D., & Kostakos, V. (2017). The Experience Sampling Method on Mobile Devices. ACM Computing Surveys, 50(6), 93:1-93:40. https://doi.org/10.1145/3123988
90. Van Damme, K., Courtois, C., Verbrugge, K., & De Marez, L. (2015a). What’s APPening to news? A mixed-method audience-centred study on mobile news consumption. Mobile Media & Communication, 3(2), 196–213. https://doi.org/10.1177/2050157914557691
91. Van Damme, K., Courtois, C., Verbrugge, K., & De Marez, L. (2015b). What’s APPening to news? A mixed-method audience-centred study on mobile news consumption. Mobile Media & Communication, 3(2), 196–213. https://doi.org/10.1177/2050157914557691
92. Viera, A. J., & Garrett, J. M. (2005). Understanding interobserver agreement: The kappa statistic. Family Medicine, 37(5), 360–363.
93. Waycott, J. (2002). Reading with new tools: An evaluation of Personal Digital Assistants as tools for reading course materials. ALT-J, 10(2), 38–50. https://doi.org/10.1080/0968776020100205
94. Weber, D., Voit, A., Kollotzek, G., & Henze, N. (2019). Annotif: A System for Annotating Mobile Notifcations in User Studies. Proceedings of the 18th International Conference on Mobile and Ubiquitous Multimedia, 1–12. https://doi.org/10.1145/3365610.3365611
95. Westermann, T., Wechsung, I., & Möller, S. (2016). Smartphone Notifications in Context: A Case Study on Receptivity by the Example of an Advertising Service. Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems, 2355–2361. https://doi.org/10.1145/2851581.2892383
96. Westlund, O. (2015). News consumption in an age of mobile media: Patterns, people, place, and participation. Mobile Media & Communication, 3(2), 151–159. https://doi.org/10.1177/2050157914563369
97. Wheatley, D., & Ferrer-Conill, R. (2020). The Temporal Nature of Mobile Push Notification Alerts: A Study of European News Outlets’ Dissemination Patterns. Digital Journalism, 0(0), 1–21. https://doi.org/10.1080/21670811.2020.1799425
98. Wohn, D. Y., & Ahmadi, M. (2019). Motivations and habits of micro-news consumption on mobile social media. Telematics and Informatics, 44, 101262. https://doi.org/10.1016/j.tele.2019.101262
99. Xu, S., Wang, Z., & Woods, K. (2019). Multitasking and Dual Motivational Systems: A Dynamic Longitudinal Study. Human Communication Research, 45(4), 371–394. https://doi.org/10.1093/hcr/hqz009
100. Yuan, F., Gao, X., & Lindqvist, J. (2017). How Busy Are You?: Predicting the Interruptibility Intensity of Mobile Users. Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 5346–5360. https://doi.org/10.1145/3025453.3025946
101. Zijlstra, F. R. H., Roe, R. A., Leonora, A. B., & Krediet, I. (1999). Temporal factors in mental work: Effects of interrupted activities. Journal of Occupational and Organizational Psychology, 72(2), 163–185. https://doi.org/10.1348/096317999166581