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Articles 31 - 60 of 23174
Full-Text Articles in Entire DC Network
Facevalue: Exploring Real-Time Self-View Overlays To Prompt Meaning-Oriented Self-Awareness In Remote Meetings, Gun Woo (Warren) Park, Anthony Tang, Fanny Chevalier
Facevalue: Exploring Real-Time Self-View Overlays To Prompt Meaning-Oriented Self-Awareness In Remote Meetings, Gun Woo (Warren) Park, Anthony Tang, Fanny Chevalier
Research Collection School Of Computing and Information Systems
In remote video meetings, visual non-verbal cues, such as facial expressions or head movements, are seen continuously but often only partially. This increases ambiguity compared to in-person settings and can cause misinterpretation or misalignment between intended and perceived meaning. Motivated by communication theories, we designed FaceValue, a technology probe that augments the self-view with private, real-time overlays. These overlays are subtle, suggestive prompts intended to help attendees reflect on how their cues might be interpreted by others. To invite personal interpretation, FaceValue avoids behavioral labeling and instead aims to support meaning-oriented self-awareness: recognizing when visible cues may unintentionally (mis)communicate intent. …
From Green Presence To Perceived Greenery: Everyday Mobility And Perceptual Availability In Singapore, Ziheng Zeng, Sonny Rosenthal, Orlando Woods
From Green Presence To Perceived Greenery: Everyday Mobility And Perceptual Availability In Singapore, Ziheng Zeng, Sonny Rosenthal, Orlando Woods
Research Collection College of Integrative Studies
Urban greenery may be abundant in transit-oriented cities, yet green presence does not necessarily become perceptually available to people moving through it. This paper distinguishes green supply, perceived greenery, and green experience, and examines the step at which greenery enters awareness during travel. The study combined 21 days of ecological momentary assessment from 68 participants in Singapore, yielding 6,794 in-trip moments, and 25 route-reconstruction interviews. A satellite normalized difference vegetation index (NDVI) provided a top-down baseline of green supply, and a street-level green view index (GVI) from Google Street View (GSV), matched to 5,824 moments, provided a co-located eye-level baseline. …
Analyst Visibility And Earnings Forecast Quality, Qiang Cheng, Tian Deng, Sterling Huang, An-Ping Lin
Analyst Visibility And Earnings Forecast Quality, Qiang Cheng, Tian Deng, Sterling Huang, An-Ping Lin
Research Collection School Of Accountancy
This study examines how a reduction in analysts’ visibility, resulting from brokerages’ switch to anonymous forecasts on Eikon, affects earnings forecast quality. Using a difference-in-differences design, we find that treatment analysts respond by issuing more accurate forecasts in the post-anonymization period. Treatment analysts who improve forecast quality the most can sustain visibility, as reflected in their coverage by the financial media, enhance their likelihood of being voted as star analysts, and induce greater client trading. These results are consistent with analysts’ incentives to offset the reduced visibility so as to advance their careers and increase trading commissions for their brokerages. …
Towards More Inclusive Ai Systems In Cities, Siew Ying Shee, Orlando Woods
Towards More Inclusive Ai Systems In Cities, Siew Ying Shee, Orlando Woods
Research Collection School of Social Sciences
Artificial Intelligence (AI) is increasingly embedded in urban infrastructures and governance, shaping how people, spaces, and futures are classified, prioritised, and managed. Yet, most AI systems are developed within a narrow set of linguistic and geopolitical contexts and exported globally, embedding particular epistemic assumptions into diverse urban environments. Even where formal inclusion metrics are met, such asymmetries can render certain populations and realities less legible within algorithmic systems. Prevailing approaches in digital inclusion—centred on fairness metrics, representation, or access—presume technologies as politically inert and bounded. Yet, the adaptive and probabilistic behaviour of contemporary AI disrupts this premise, challenging the idea …
Learning 1-Bit Lidar-Based Localization With Auxiliary Objective, Kaijie Yin, Zhiyuan Zhang, Tian Gao, Wentao Zhu, Cheng-Zhong Xu, Hui Kong
Learning 1-Bit Lidar-Based Localization With Auxiliary Objective, Kaijie Yin, Zhiyuan Zhang, Tian Gao, Wentao Zhu, Cheng-Zhong Xu, Hui Kong
Research Collection School Of Computing and Information Systems
6-DoF LiDAR-based localization is a fundamental capability for autonomous systems operating in large-scale outdoor environments. Many deep-learning-based localization methods have achieved promising performance so far. However, as one of the always-on modules competing for limited on-board computational resources, the localization module is expected to consume only a small portion of the overall compute budget. Most existing learning-based methods are still too heavy for this purpose. In contrast, binary neural networks (BNNs) offer an appealing solution, but the 1-bit compression causes severe information loss and performance drop. In this paper, we address this challenge by proposing Binarized LiDAR-based Localization (BiLoc), the …
Graph Perturbation Analysis For Subgraph Counting, Hanhua Xiao, Yuchen Li, Kyriakos Mouratidis
Graph Perturbation Analysis For Subgraph Counting, Hanhua Xiao, Yuchen Li, Kyriakos Mouratidis
PhD Student’s Publications Collection
Subgraph counting, which involves determining the frequency of a query graph within a data graph, has numerous applications such as query optimization, fraud detection, and evaluating the expressiveness of graph neural networks. Despite its importance, there has been no systematic study on the impact of adversarial graph perturbations on subgraph counts. In this work, we examine the kSub problem, which aims to identify k edge additions that maximize the count of a query graph. We prove that kSub is intractable due to its NP-hardness, even for constant approximation. To address this, we relax the problem into a top-k selection, termed …
Llm-As-A-Judge For Software Engineering: Literature Review, Vision, And The Road Ahead, Junda He, Jieke Shi, Terry Yue Zhuo, Christoph Treude, Jiamou Sun, Zhenchang Xing, Xiaoning Du, David Lo
Llm-As-A-Judge For Software Engineering: Literature Review, Vision, And The Road Ahead, Junda He, Jieke Shi, Terry Yue Zhuo, Christoph Treude, Jiamou Sun, Zhenchang Xing, Xiaoning Du, David Lo
Research Collection School Of Computing and Information Systems
The rapid integration of Large Language Models (LLMs) into software engineering (SE) has revolutionized tasks from code generation to program repair, producing a massive volume of software artifacts. This surge in automated creation has exposed a critical bottleneck: the lack of scalable and reliable methods to evaluate the quality of these outputs. Human evaluation, while effective, is very costly and time-consuming. Traditional automated metrics like BLEU rely on high-quality references and struggle to capture nuanced aspects of software quality, such as readability and usefulness. In response, the LLM-as-a-Judge paradigm, which employs LLMs for automated evaluation, has emerged. This approach leverages …
Tiny Treasures: Cloves In Early Modern English Literature, Emily Soon
Tiny Treasures: Cloves In Early Modern English Literature, Emily Soon
Research Collection School of Social Sciences
This Southeast Asian spice not only sparked fierce international competition, but also featured within the literature of the Global Renaissance.
Success Of New Ideas In Online Platforms: An Idea Network Perspective, Yimei Zhou, Qian Tang, Vincent Z.W. Mack Mack, Shao Yi Liaw
Success Of New Ideas In Online Platforms: An Idea Network Perspective, Yimei Zhou, Qian Tang, Vincent Z.W. Mack Mack, Shao Yi Liaw
Research Collection School Of Computing and Information Systems
On online platforms, new ideas often emerge by recombining existing ones within idea networks. Unlike traditional knowledge networks, idea networks represent curated, meaning-based associations among ideas, offering a distinct lens on recombination. Drawing upon a hypergraph perspective, we investigate how new idea success depends on their structural and content attributes, and how collaborative participation shapes these attributes. Using data from an ideation platform, we find that both structural embeddedness and bridging benefit new idea success. Content diversity has no direct effect, but it amplifies the benefits of bridging while constraining those of embeddedness. Both crowd contributions and ideator expertise strengthen …
Leading The Change: Staff-Driven Ai Transformation In Smu Libraries’ Collection Team, Siew Khim Lim, Fion Goh
Leading The Change: Staff-Driven Ai Transformation In Smu Libraries’ Collection Team, Siew Khim Lim, Fion Goh
Research Collection Library
No abstract provided.
From Open Banking To Banking-As-A-Service: Regulatory Challenges In The Evolution Of Financial Intermediation, Nydia Remolina Leon
From Open Banking To Banking-As-A-Service: Regulatory Challenges In The Evolution Of Financial Intermediation, Nydia Remolina Leon
Research Collection Yong Pung How School Of Law
Over the past decade, financial innovation has moved from open banking, centred on consumer-permissioned data sharing, to banking-as-a-service (BaaS), which modularises core banking functions through application programming interfaces. This shift allows fintechs and non-financial platforms to embed financial products seamlessly, reducing transaction costs and fostering innovation. Yet the 2024 collapse of Synapse in the United States exposed the fragility of this model when intermediaries operate outside robust oversight, leaving consumers without recourse and revealing liability fragmentation and regulatory blind spots. This paper distinguishes BaaS from open banking, open finance, and embedded finance, and maps leading global models – from bank-led …
Ai-Ready Libraries Require Ai-Ready Librarians: Building Organisational Capability For Digital Transformation, Salihin Mohammed Ali
Ai-Ready Libraries Require Ai-Ready Librarians: Building Organisational Capability For Digital Transformation, Salihin Mohammed Ali
Research Collection Library
Academic libraries worldwide are rapidly experimenting with artificial intelligence (AI) to enhance research, learning, discovery, operations, and user engagement. However, many institutions continue to approach AI adoption primarily through isolated pilots, individual experimentation, or technology-centric initiatives. While these efforts generate innovation, they often struggle to scale sustainably without corresponding organisational capability development. This presentation argues that AI-ready libraries require AI-ready librarians and proposes an organisational capability approach for sustainable AI transformation in academic libraries. Drawing from the development of a library-wide AI strategy plans at Singapore Management University, the presentation explores how AI capability-building can be operationalised across diverse functional …
Global Prevalence Of Depression Among University Students: A Comprehensive Umbrella Review, Gilda Yun Kai Sam, Xun Ci Soh, Harshitha Balaji, Gabriel X. D. Tan, Shu Fen Diong, Meilan Hu, Andree Hartanto, Nadyanna M. Majeed
Global Prevalence Of Depression Among University Students: A Comprehensive Umbrella Review, Gilda Yun Kai Sam, Xun Ci Soh, Harshitha Balaji, Gabriel X. D. Tan, Shu Fen Diong, Meilan Hu, Andree Hartanto, Nadyanna M. Majeed
Research Collection School of Social Sciences
Depression has become a major concern for educational institutes due to its increasing incidence and detrimental impacts on students’ well-being. However, its global prevalence in the context of tertiary education remains unclear. This umbrella review summarised existing meta-analyses and systematic reviews to examine the worldwide prevalence of depression among university students. Several sociodemographic and methodological factors, including differences in depression prevalence before, during, and after COVID-19, were examined as moderators. Structured and exhaustive searches were conducted in five bibliographic databases and five journals, alongside two sources of grey literature. A total of 61 meta-analyses and systematic reviews were included in …
Llm-Based Early Rumor Detection With Imitation Agent, Fengzhu Zeng, Qian Shao, Ling Cheng, Wei Gao, Shih-Fen Cheng, Jing Ma, Cheng Niu
Llm-Based Early Rumor Detection With Imitation Agent, Fengzhu Zeng, Qian Shao, Ling Cheng, Wei Gao, Shih-Fen Cheng, Jing Ma, Cheng Niu
Research Collection School Of Computing and Information Systems
Early Rumor Detection (EARD) aims to identify the earliest point at which a claim can be accurately classified based on a sequence of social media posts. This is especially challenging in data-scarce settings. While Large Language Models (LLMs) perform well in few-shot NLP tasks, they are not well-suited for time-series data and are computationally expensive for both training and inference. In this work, we propose a novel EARD framework that combines an autonomous agent and an LLM-based detection model, where the agent acts as a reliable decision-maker for \textit{early time point determination}, while the LLM serves as a powerful \textit{rumor …
Promotion Architecture: A Deal Fairness Model Of Restricted Price Promotions, Shangwen Yi, David Hardisty, Dale Griffin, Thomas Allard
Promotion Architecture: A Deal Fairness Model Of Restricted Price Promotions, Shangwen Yi, David Hardisty, Dale Griffin, Thomas Allard
Research Collection Lee Kong Chian School Of Business
This research examines the effectiveness of two common types of restricted price promotions: threshold promotions (conditional on spending more than a threshold amount; e.g., “Get $5 off on orders of $10 or more”) and capped promotions (limited to a maximum dollar value; e.g., “Get 50% off, up to $5 per order”). Results from seven pre-registered studies, including one field study, show that threshold promotions lead to higher purchase intentions and conversion rates (but potentially lower purchase amounts) than comparable capped promotions—even though capped promotions are equivalent in maximal economic savings for the consumer—when the trigger value (the spending amount at …
Gaming The Marketplace: Consumer Opportunism And Beliefs About Societal Hierarchy, Shilpa Madan, Aparna Labroo, Constantine S. Katsikeas
Gaming The Marketplace: Consumer Opportunism And Beliefs About Societal Hierarchy, Shilpa Madan, Aparna Labroo, Constantine S. Katsikeas
Research Collection Lee Kong Chian School Of Business
Consumers often behave opportunistically, taking more than what fair marketplace exchange warrants (e.g., taking excess samples, returning used items). While each individual transgression may be minor, cumulatively they can undermine firm profitability. Thus, addressing consumer opportunism is an important managerial concern. We identify a novel antecedent of consumer opportunism: consumers’ acceptance of societal hierarchy (i.e., power distance belief [PDB]), including firms’ higher position in it than consumers. Nine studies (plus two supplementary studies) employing archival, correlational, and experimental data provide converging evidence that, in marketplace interactions, this belief evokes a need to feel clever (i.e., to feel smart and knowledgeable …
When Your Neighbours Are A Reminder Of Your Ageing, Cynthia Tan, Yi Wen (Chen Yiwen) Tan
When Your Neighbours Are A Reminder Of Your Ageing, Cynthia Tan, Yi Wen (Chen Yiwen) Tan
ROSA Journal Articles and Publications
In a commentary, Cynthia Tan, a retired senior corporate leader, and Tan Yi Wen, a Senior Research Fellow at SMU’s Centre for Research on Successful Ageing (ROSA), questioned whether the low demand for community care apartments is because seniors do not want only other seniors for company. They noted that most older people do not spend their days dwelling on ageing until everyone around them reminds them that they are growing old. They added that prolonged exposure to such an environment may carry subtle emotional and psychological consequences. Citing a national survey by ROSA, the writers mentioned that eight in …
Bank Competition Amid Digital Disruption: Implications For Financial Inclusion, Erica Xuewei Jiang, Gloria Yang Yu, Jinyuan Zhang
Bank Competition Amid Digital Disruption: Implications For Financial Inclusion, Erica Xuewei Jiang, Gloria Yang Yu, Jinyuan Zhang
Research Collection Lee Kong Chian School Of Business
We examine how digital disruption affects bank competition using the staggered rollout of 3G mobile networks. 3G expansion increased mobile banking adoption among tech-savvy households, reducing branch networks—especially in younger counties. Banks' strategies diverged: Less branch-reliant banks closed branches and competed on price, while more branch-reliant banks maintained branches but raised spreads. A structural model shows that perceived digital service improvements among younger consumers drove these shifts, reducing welfare for older savers. Counterfactuals demonstrate that subsidizing adoption for older savers can cost-effectively reduce these disparities, facilitating a smoother digital transition.
Dynamics Of High-Growth Young Firms And The Role Of Venture Capitalists, Yoshiki Ando
Dynamics Of High-Growth Young Firms And The Role Of Venture Capitalists, Yoshiki Ando
Research Collection School Of Economics
Motivated by the substantial growth and upfront investments of venture capital (VC)-backed firms observed in administrative US Census data, this study develops a life-cycle firm dynamics model. In the model, startups choose the source of financing from VC, angel investors, or banks, depending on their growth potential, and invest in innovation. The calibrated model explains the life-cycle dynamics of firms with different sources of financing and suggests that venture capitalists' managerial advice accounts for around 22% of the growth in VC-backed firms. A counterfactual economy without VC financing would experience an aggregate consumption loss of around 0.46%.
Semiparametric Cointegrating Rank Selection For Curved Cross-Section Time Series, Peter C. B. Phillips
Semiparametric Cointegrating Rank Selection For Curved Cross-Section Time Series, Peter C. B. Phillips
Research Collection School Of Economics
Cointegrating rank selection is studied in a function space reduced rank regression where the data are time series of cross-section curves. Consistent cointegrating rank estimation is developed using information criteria extended to curve time series environments. The asymptotic theory involves two-parameter Gaussian processes that generalise the standard limit processes involved in cointegrating regressions. Simulations provide evidence of the effectiveness of consistent rank selection by the BIC criterion and the tendency of AIC to overestimate order as in standard lag order selection in autoregression, as well as in reduced rank regression with multiple time series.
Singapore In Global Value Chains: Implications Of The Trump Ii Tariffs, Pao-Li Chang, Ruoqing Chen
Singapore In Global Value Chains: Implications Of The Trump Ii Tariffs, Pao-Li Chang, Ruoqing Chen
Research Collection School Of Economics
This paper examines Singapore’s structural position in global value chains (GVCs) and the implications of the second Trump administration’s tariff escalation for Singapore and the broader ASEAN region. We proceed in three parts. First, using the ADB Multi-Regional Input–Output (MRIO) tables for 2019 and 2024, we characterise Singapore’s GVC participation and position. Singapore is the most GVCintensive economy in ASEAN, with nearly half of its gross exports comprising foreign value-added and a markedly downstream orientation. China is its dominant upstream partner across manufacturing and services—intermediating over 27% of foreign content in electronics and over 10% in chemicals—while Malaysia, Taiwan, and …
Marital Stability And Intrahousehold Inequality, Tomoki Fujii, Xirong Lin, Jacob Penglase
Marital Stability And Intrahousehold Inequality, Tomoki Fujii, Xirong Lin, Jacob Penglase
Research Collection School Of Economics
We study what predicts marital instability using a unique dataset from Japan with detailed measures of spouses’ consumption, savings, labor supply, satisfaction, and marriage-market conditions. We combine descriptive survival and event-study analyses with several econometric and machine-learning approaches, including Cox proportional-hazards models and DynForest, a method designed for survival data with time-varying covariates. Across these approaches, match quality, household resources, time use, stated satisfaction, and marriage-market conditions all contain predictive information. Our main contribution is to show that intrahousehold consumption allocation matters, highlighting information that is missed by standard demographic, time use, and income measures. We relate these findings to …
The Interplay Of Interdependence And Correlation In Bilateral Trade, Takashi Kunimoto, Cuiling Zhang
The Interplay Of Interdependence And Correlation In Bilateral Trade, Takashi Kunimoto, Cuiling Zhang
Research Collection School Of Economics
Following Crémer and McLean (1985, 1988) for finite type spaces and McAfee and Reny (1992) for continuous ones, we establish two respective sufficient conditions for the existence of efficient, ex ante budget-balanced mechanisms satisfying Bayesian incentive compatibility (BIC) and interim individual rationality (IIR) in bilateral trade settings with interdependent values and correlated beliefs. We then utilize the ex ante welfare (EAW) condition proposed by Kunimoto and Zhang (2026), which is necessary for the stricter requirement of ex post budget balance. We prove that while the EAW condition is sufficient in a two-type model and generalizes existing conditions in the literature, …
How Followers Respond To Leader Differentiation: The Importance Of Considering All Leader Differentiation Properties, Yuchuan Liu, Gary John Greguras
How Followers Respond To Leader Differentiation: The Importance Of Considering All Leader Differentiation Properties, Yuchuan Liu, Gary John Greguras
Research Collection Lee Kong Chian School Of Business
A central tenet of many leadership theories is that leaders treat their followers differently. Although leader differentiation is ubiquitous, its effects on leaders and followers are not well understood and theory and research have not simultaneously considered its three key properties: Leader–member exchange (LMX) differentiation, LMX quality, and LMX social comparison. We developed a theoretical model in which these three properties interact to influence followers’ supervisory interactional justice perceptions and subsequently their supervisor-directed deviance and supervisor-directed organizational citizenship behaviors (OCBs). To test our model, we conducted a pre-registered experiment (Study 1), a single-level, multi-wave study (Study 2), and a multilevel, …
Connectivity And Selective Rural Migration, Lin Ma, Yuan Mei, Qunfeng Wu, Mingzhi Xu
Connectivity And Selective Rural Migration, Lin Ma, Yuan Mei, Qunfeng Wu, Mingzhi Xu
Research Collection School Of Economics
How does infrastructure shape rural development? Using household panel data from a nationally representative sample of Chinese villages, matched to high-resolution highway maps, we find that road expansion between 2000 and 2015 operates mainly through reallocation, with less productive farmers scaling down or exiting and more productive farmers remaining and expanding. We quantify the aggregate and distributional consequences in a dynamic spatial equilibrium model with heterogeneous households and endogenous migration. Improved connectivity not only accelerates urbanization but also increases aggregate rural output by 2.2%–5.3% in the long run, even as the rural workforce declines.
Casual Killing In The Home: Ecological Citizenship And The Micro-Geopolitics Of Mosquito Cohabitation, Orlando Woods, Junxi Qian
Casual Killing In The Home: Ecological Citizenship And The Micro-Geopolitics Of Mosquito Cohabitation, Orlando Woods, Junxi Qian
Research Collection College of Integrative Studies
This article explores how the visceral acts of being bitten by and killing mosquitoes can underpin the formation of ecological citizenship. This form of citizenship is premised on human-nature entanglement and raises questions concerning how the rights and responsibilities stemming from such entanglement become distributed across the public and private domains. As a space in which mosquito cohabitation is contested daily, the home is a key site through which ecological citizenship can be forged and theoretical debates concerning urban political ecology can be extended. Human-mosquito entanglements in the home can reveal the limits of public pest management strategies, the partiality …
Efficient And Universal Watermarking For Llm-Generated Code Detection, Boquan Li, Zirui Fu, Mengdi Zhang, Peixin Zhang, Jun Sun, Xingmei Wang
Efficient And Universal Watermarking For Llm-Generated Code Detection, Boquan Li, Zirui Fu, Mengdi Zhang, Peixin Zhang, Jun Sun, Xingmei Wang
Research Collection School Of Computing and Information Systems
Large language models (LLMs) have significantly enhanced the usability of AI-generated code, providing effective assistance to programmers. This advancement also raises ethical and legal concerns, such as academic dishonesty and the generation of malicious code. For accountability, it is imperative to detect whether a piece of code is AI-generated. Watermarking is broadly considered a promising solution and has been successfully applied to identify LLM-generated text. However, existing efforts on code are far from ideal, suffering from limited universality and excessive time and memory consumption. In this work, we propose a plugand- play watermarking approach for AI-generated code detection, named ACW …
Continuous Query For Top-K Maximal Sum Intervals Over Streaming Data, Zhongshuai Zhang, Xiaochun Yang, Baihua Zheng, Rui Zhu, Haomin Li, Bin Wang
Continuous Query For Top-K Maximal Sum Intervals Over Streaming Data, Zhongshuai Zhang, Xiaochun Yang, Baihua Zheng, Rui Zhu, Haomin Li, Bin Wang
Research Collection School Of Computing and Information Systems
The continuous identification of top-k maximal sum intervals using a sliding window over a data stream is a critical operation for applications in IoT and beyond. A maximal sum interval is a non-overlapping, contiguous subsequence with the maximal sum in a sequence of signed values. Existing algorithms are ill-suited for streaming contexts: they either exhaustively enumerate all intervals even for small k values, or depend on indexes that require frequent and costly restructuring. We propose a novel partition-based strategy. Our core insight is a partitioning scheme that guarantees that any maximal sum interval is fully contained within a single partition, …
Dynamic Spectral Denoising With Global-Context Attention For Multi-Behavior Recommendation, Miaomiao Cai, Yunshan Ma, Fangqi Zhu, Junfeng Fang, Zhijie Zhang, Zhiyong Cheng, Xiang Wang, See-Kiong Ng
Dynamic Spectral Denoising With Global-Context Attention For Multi-Behavior Recommendation, Miaomiao Cai, Yunshan Ma, Fangqi Zhu, Junfeng Fang, Zhijie Zhang, Zhiyong Cheng, Xiang Wang, See-Kiong Ng
Research Collection School Of Computing and Information Systems
Multi-behavior recommendation improves target-behavior predic-tion by exploiting heterogeneous auxiliary feedback (e.g., view,collect, and cart), yet its robustness is often undermined by behavior-dependent noise and inconsistency. We argue that the key bottle-neck is not merely noisy behaviors, but a representation-level failurecaused by two coupled heterogeneities. First, intra-behavior rep-resentation entanglement arises when multi-hop propagationblends incidental signals with true preferences in the embeddingspace. This entanglement renders coarse spatial denoising inef-fective, since it cannot suppress noise without sacrificing weak-but-informative niche signals. Second, inter-behavior reliabilityheterogeneity complicates cross-behavior fusion, as the predic-tive value of auxiliary behaviors varies substantially across usersand contexts. Without reliability calibration, aggregation can …
Approximation And Learning-Based Algorithms For Influence Maximization In Multilayer Social Networks, Xueqin Chang, Ruize Liu, Qing Liu, Baihua Zheng, Yunjun Gao
Approximation And Learning-Based Algorithms For Influence Maximization In Multilayer Social Networks, Xueqin Chang, Ruize Liu, Qing Liu, Baihua Zheng, Yunjun Gao
Research Collection School Of Computing and Information Systems
Motivated by the observation that users in the real world often engage across multiple social networks simultaneously, we study the problem of influence maximization in multilayer social networks (Mlim), aiming to select a small set of nodes that maximizes the total influence spread across all layers. To this end, we introduce a hybrid propagation model that jointly captures layer-specific diffusion dynamics and probabilistic cross-layer propagation. Based on this model, we formally define the Mlim problem and establish its NP-hardness, monotonicity, and submodularity. To address the Mlim problem, we first propose a greedy baseline Mlim-Greedy, which achieves a (1-1/e) approximation. Since …