AdverTiming Matters: Examining User Ad Consumption for Effective Ad Allocations on Social Media

Saha, Koustuv; Liu, Yozen; Vincent, Nicholas; Chowdhury, Farhan Asif; Neves, Lucio Pereira; Shah, Neil; Bos, Maarten W.

doi:10.1145/3411764.3445394

Cited by 14 publications

(10 citation statements)

References 84 publications

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“…We do not infer the exact reason for suspension for individual users; rather, we quantify violations at tweet level. Future research can use causal inference methods like matching (Saha and Sharma 2020) to minimize confounds and draw causal claims about why certain accounts were suspended. Moreover, we utilize several publicly available datasets that might suffer from biases.…”

Section: Discussionmentioning

confidence: 99%

“…We calculate effect size (Cohen's d) and use independent sample t-tests to evaluate statistical significance in the differences. We perform Koglomorov-Smirnov (KS) test to test against the null hypothesis that the distribution of suspension rules for the Suspended and Control users are drawn from the same distribution (Saha et al 2021). We summarize these differences in Table 2.…”

Section: Rq1: Inferring Suspension Reasonmentioning

confidence: 99%

See 1 more Smart Citation

Examining factors associated with Twitter account suspension following the 2020 U.S. presidential election

Chowdhury¹,

Saha²,

Hasan³

et al. 2021

Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

Self Cite

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Online social media enables mass-level, transparent, and democratized discussion on numerous socio-political issues. Due to such openness, these platforms often endure manipulation and misinformation -leading to negative impacts. To prevent such harmful activities, platform moderators employ countermeasures to safeguard against actors violating their rules. However, the correlation between publicly outlined policies and employed action is less clear to general people. In this work, we examine violations and subsequent moderations related to the 2020 U.S. President Election discussion on Twitter. We focus on quantifying plausible reasons for the suspension, drawing on Twitter's rules and policies by identifying suspended users (Case) and comparing their activities and properties with (yet) non-suspended (Control ) users. Using a dataset of 240M election-related tweets made by 21M unique users, we observe that Suspended users violate Twitter's rules at a higher rate (statistically significant) than Control users across all the considered aspects -hate speech, offensiveness, spamming, and civic integrity. Moreover, through the lens of Twitter's suspension mechanism, we qualitatively examine the targeted topics for manipulation.

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Section: Discussionmentioning

confidence: 99%

Section: Rq1: Inferring Suspension Reasonmentioning

confidence: 99%

Examining factors associated with Twitter account suspension following the 2020 U.S. presidential election

Chowdhury¹,

Saha²,

Hasan³

et al. 2021

Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

Self Cite

View full text Add to dashboard Cite

show abstract

“…For example, recommender systems could be augmented with exploration metrics to measure whether users are generally exploratory, and whether they are in an exploratory phase, and tailor recommendations accordingly. Indeed, recent work on ad timing indicates that this sort of temporal information can significantly impact receptiveness to recommendations (Saha et al 2021). Furthermore, previous work has demonstrated that recommendations guided by heterogeneity are more likely to be satisfactory (Zhang et al 2012;Schedl and Hauger 2015) and lead to positive retention outcomes (Anderson et al 2020a), although there are trade-offs in engagement made when increasing consumption diversity (Holtz et al 2020).…”

Section: Discussionmentioning

confidence: 99%

The Dynamics of Exploration on Spotify

Mok

Way

Maystre

et al. 2022

ICWSM

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Digital media platforms give users access to enormous amounts of content that they must explore to avoid boredom and satisfy their needs for heterogeneity. Existing strands of work across psychology, marketing, computer science, and music underscore the importance of the lifecycle to understanding exploratory behavior, but they are also often inconsistent with each other. In this study, we examine how users explore online content on Spotify over time, whether by discovering entirely novel music or by refreshing their listening habits from one time frame to the next. We find clear differences between users at different points of their off-platform lifecycles, with younger listeners consistently exploring unknown content less and exploiting known content more. Across their on-platform histories, users also explore in bursts by following seasonal cycles and exploratory phases. We also find that these patterns of exploration do not translate to other notions of heterogeneity like diversity; notably, younger listeners are more diverse in their consumption despite exploring less. Exploration and diversity thus capture different ways in which people find variety, potentially accounting for the inconsistencies in existing work. Together, these nuanced dynamics of exploration suggest that online platforms may be better poised to support users by incorporating different measures of heterogeneous consumption.

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“…(Lamba and Shah 2019;Kaghazgaran et al 2020) characterize and statistically model consumption behaviors of Direct Snaps and Story Snaps, respectively. Several works (Tang et al 2020;Saha et al 2021) also propose approaches to model ad response and user churn phenomena on Snapchat.…”

Section: The Snapchat Platformmentioning

confidence: 99%

Online Communication Shifts in the Midst of the Covid-19 Pandemic: A Case Study on Snapchat

Yang

Wang

Pierce

et al. 2021

ICWSM

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The Covid-19 pandemic has created large shifts in how people stay connected with each other in lieu of social distancing and isolation measures. More and more, individuals have turned to online communications as a necessary replacement for in-person interaction. Despite this, the research community has little understanding of how online communications have been influenced by the offline impacts of Covid-19. Our work touches upon this topic. Specifically, we study research questions around the impact of Covid-19 on online public and private sharing propensity, its influence on online communication homophily, and correlations between online communication and offline case severity in the United States. To do so, we study the usage patterns of 79 million US-based users on Snapchat, a large, leading mobile multimedia-driven social sharing platform. Our findings suggest that Covid-19 has increased propensity to privately communicate with friends, while decreasing propensity to publicly share content when users are out-and-about. Moreover, online communications have observed a marked decrease in baseline homophily across locations, ages and genders, with relative increases in cross-group communications. Finally, we observe that increased offline positive Covid-19 case severity in US states is associated with widening gaps between across-state and within-state communication increases after the onset of Covid-19, as well as marked declines in public sharing. We hope our findings drive further interest and work on online communication changes during pandemics and other extended times of crisis.

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AdverTiming Matters: Examining User Ad Consumption for Effective Ad Allocations on Social Media

Cited by 14 publications

References 84 publications

Examining factors associated with Twitter account suspension following the 2020 U.S. presidential election

Examining factors associated with Twitter account suspension following the 2020 U.S. presidential election

The Dynamics of Exploration on Spotify

Online Communication Shifts in the Midst of the Covid-19 Pandemic: A Case Study on Snapchat

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