2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)最新文献

Reconstructing and Analyzing the Transnational Human Trafficking Network 跨国人口贩运网络的重构与分析

2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2019-08-01 DOI: 10.1145/3341161.3342879

Mitchell Goist, T. H. Chen, C. Boylan

引用次数: 4

Collecting Representative Social Media Samples from a Search Engine by Adaptive Query Generation 通过自适应查询生成从搜索引擎中收集具有代表性的社交媒体样本

2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2019-08-01 DOI: 10.1145/3341161.3342924

Virgile Landeiro, A. Culotta

引用次数: 0

Multi-Factor Congressional Vote Prediction 多因素国会投票预测

2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2019-08-01 DOI: 10.1145/3341161.3342884

Hamid Karimi, Tyler Derr, Aaron Brookhouse, Jiliang Tang

{"title":"Multi-Factor Congressional Vote Prediction","authors":"Hamid Karimi, Tyler Derr, Aaron Brookhouse, Jiliang Tang","doi":"10.1145/3341161.3342884","DOIUrl":"https://doi.org/10.1145/3341161.3342884","url":null,"abstract":"In recent times we have seen a trend of having the ideologies of the two dominant political parties in the U.S. growing further and further apart. Simultaneously we have entered the age of big data raising enormous interest in computational approaches to solve problems in many domains such as political elections. However, an overlooked problem lies in predicting what happens once our elected officials take office, more specifically, predicting the congressional votes, which are perhaps the most influential decisions being made in the U.S. This, nevertheless, is far from a trivial task, since the congressional system is highly complex and heavily influenced by both ideological and social factors. Thus, dedicated efforts are required to first effectively identify and represent these factors, then furthermore capture the interactions between them. To this end, we proposed a robust end-to-end framework Multi-Factor Congressional Vote Prediction (MFCVP) that defines and encodes features from indicative ideological factors while also extracting novel social features. This allows for a principled expressive representation of the complex system, which ultimately leads to MFCVP making accurate vote predictions. Experimental results on a dataset from the U.S. House of Representatives shows the superiority of MFCVP to several representatives approaches when predicting votes for individual representatives and also the overall outcome of the bill voted on. Finally, we perform a factor analysis to understand the effectiveness and interplay between the different factors.","PeriodicalId":403360,"journal":{"name":"2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"222 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120854561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 24

Through The Eyes of A Poet: Classical Poetry Recommendation with Visual Input on Social Media 通过诗人的眼睛:社交媒体上视觉输入的古典诗歌推荐

2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2019-08-01 DOI: 10.1145/3341161.3342885

D. Zhang, Bo Ni, Qiyu Zhi, Thomas Plummer, Qi Li, Hao Zheng, Qingkai Zeng, Yang Zhang, Dong Wang

{"title":"Through The Eyes of A Poet: Classical Poetry Recommendation with Visual Input on Social Media","authors":"D. Zhang, Bo Ni, Qiyu Zhi, Thomas Plummer, Qi Li, Hao Zheng, Qingkai Zeng, Yang Zhang, Dong Wang","doi":"10.1145/3341161.3342885","DOIUrl":"https://doi.org/10.1145/3341161.3342885","url":null,"abstract":"With the increasing popularity of portable devices with cameras (e.g., smartphones and tablets) and ubiquitous Internet connectivity, travelers can share their instant experience during the travel by posting photos they took to social media platforms. In this paper, we present a new image-driven poetry recommender system that takes a traveler's photo as input and recommends classical poems that can enrich the photo with aesthetically pleasing quotes from the poems. Three critical challenges exist to solve this new problem: i) how to extract the implicit artistic conception embedded in both poems and images? ii) How to identify the salient objects in the image without knowing the creator's intent? iii) How to accommodate the diverse user perceptions of the image and make a diversified poetry recommendation? The proposed iPoemRec system jointly addresses the above challenges by developing heterogeneous information network and neural embedding techniques. Evaluation results from real-world datasets and a user study demonstrate that our system can recommend highly relevant classical poems for a given photo and receive significantly higher user ratings compared to the state-of-the-art baselines.","PeriodicalId":403360,"journal":{"name":"2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116599138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Evaluation of Extremist Cohesion in a Darknet Forum Using ERGM and LDA 基于ERGM和LDA的暗网论坛极值内聚评价

2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2019-08-01 DOI: 10.1145/3341161.3343532

Mohammed Rashed, J. Piorkowski, I. McCulloh

引用次数: 3

Topic Enhanced Word Embedding for Toxic Content Detection in Q&A Sites 主题增强词嵌入有毒内容检测在问答网站

2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2019-08-01 DOI: 10.1145/3341161.3345332

Do Yeon Kim, Xiaohan Li, Sheng Wang, Yunying Zhuo, R. Lee

引用次数: 9

Building a Task Blacklist for Online Social Platforms 构建网络社交平台任务黑名单

2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2019-08-01 DOI: 10.1145/3341161.3343705

Trang Ha, Quyen Hoang, Kyumin Lee

引用次数: 0

Detection of Topical Influence in Social Networks via Granger-Causal Inference: A Twitter Case Study 基于granger因果推理的社交网络话题影响检测:以Twitter为例

2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2019-08-01 DOI: 10.1145/3341161.3345024

Jan Hauffa, Wolfgang Bräu, Georg Groh

引用次数: 3

Hierarchical Multi-Armed Bandits for Discovering Hidden Populations 发现隐藏人口的分层多武装土匪

2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2019-08-01 DOI: 10.1145/3341161.3342880

Suhansanu Kumar, Heting Gao, Changyu Wang, K. Chang, H. Sundaram

{"title":"Hierarchical Multi-Armed Bandits for Discovering Hidden Populations","authors":"Suhansanu Kumar, Heting Gao, Changyu Wang, K. Chang, H. Sundaram","doi":"10.1145/3341161.3342880","DOIUrl":"https://doi.org/10.1145/3341161.3342880","url":null,"abstract":"This paper proposes a novel algorithm to discover hidden individuals in a social network. The problem is increasingly important for social scientists as the populations (e.g., individuals with mental illness) that they study converse online. Since these populations do not use the category (e.g., mental illness) to self-describe, directly querying with text is non-trivial. To by-pass the limitations of network and query re-writing frameworks, we focus on identifying hidden populations through attributed search. We propose a hierarchical Multi-Arm Bandit (DT-TMP) sampler that uses a decision tree coupled with reinforcement learning to query the combinatorial attributed search space by exploring and expanding along high yielding decision-tree branches. A comprehensive set of experiments over a suite of twelve sampling tasks on three online web platforms, and three offline entity datasets reveals that DT-TMP outperforms all baseline samplers by upto a margin of 54% on Twitter and 48% on RateMDs. An extensive ablation study confirms DT-TMP's superior performance under different sampling scenarios.","PeriodicalId":403360,"journal":{"name":"2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124107309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A Novel Methodology for Improving Election Poll Prediction Using Time-Aware Polling 一种利用时间感知民意测验改进选举民意预测的新方法

2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2019-08-01 DOI: 10.1145/3341161.3342900

Alexandru Topîrceanu, R. Precup

{"title":"A Novel Methodology for Improving Election Poll Prediction Using Time-Aware Polling","authors":"Alexandru Topîrceanu, R. Precup","doi":"10.1145/3341161.3342900","DOIUrl":"https://doi.org/10.1145/3341161.3342900","url":null,"abstract":"Multiple poll forecasting solutions, based on statistics and economic indices, have been proposed over time, but, as we better understand diffusion phenomena, we know that temporal characteristics provide even more uncertainty. As such, current literature is not yet able to define truly reliable models for the evolution of political opinion, marketing preferences, or social unrest. Inspired by micro-scale opinion dynamics, we develop an original time-aware (TA) methodology which is able to improve the prediction of opinion distribution, by modeling opinion as a function which spikes up when opinion is expressed, and slowly dampens down otherwise. After a parametric analysis, we validate our TA method on survey data from the US presidential elections of 2012 and 2016. By comparing our time-aware method (TA) with classic survey averaging (SA), and cumulative vote counting (CC), we find our method is substantially closer to the real election outcomes. On average, we measure that SA is 6.3% off, CC is 5.6% off, while TA is only 1.5% off from the final registered election outcomes; this difference translates into an ≈ 75% prediction improvement of our TA method. As our work falls in line with studies on the microscopic temporal dynamics of social networks, we find evidence of how macroscopic prediction can be improved using time-awareness.","PeriodicalId":403360,"journal":{"name":"2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124114166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2