ToWikify

Paper	Related Paper	Student Andrew ID	Link to Comparison
Yang_et_al_Modeling_Information_Diffusion_in_Implicit_Networks	Inferring the Diffusion and Evolution of Topics in Social Communities [1]	Bliu1	Compare_Yang_et_al_Modeling_Information_Diffusion_in_Implicit_Networks_and_Inferring_the_Diffusion_and_Evolution_of_Topics_in_Social_Communities
Zheleva_ACM_2009	Geographic routing in social networks [2]
Y._Borghol_et_al._Performance_Evaluation_68_2011	The Untold Story of the Clones: Content-agnostic Factors that Impact YouTube Video Popularity [3]	tinghuiz	Compare Y. Borghol et al. 2011 and The Untold Story of the Clones: Content-agnostic Factors that Impact YouTube Video Popularity
Zheleva_and_Getoor,_WWW2009	Preserving the privacy of sensitive relationships in graph data. PinKDD, 2007 [4]	zsheikh	Zheleva_and_Getoor,_WWW2009,_PinKDD2007_paper_comparison
Vladimir_Ouzienko,_Prediction_of_Attributes_and_Links_in_Temporal_Social_Networks	Introduction to stochastic actor-based models for network dynamics [5]
Miller_et_al_ICWSM_2011	Can predicate-argument structures be used for contextual opinion retrieval from blogs? [6]	austinma
Ritter_et_al,_EMNLP_2011._Named_Entity_Recognition_in_Tweets:_An_Experimental_Study	Event discovery in social media feeds [7]
Ritter_et_al_NAACL_2010._Unsupervised_Modeling_of_Twitter_Conversations	Catching the drift: Probabilistic content models, with applications to generation and summarization [8]
Modeling_Contagion_Through_Facebook_News_Feed	Cascading Behavior in Large Blog Graphs [9]	thoang	Compare Modeling_Contagion_Through_Facebook_News_Feed and Cascading Behavior in Large Blog Graphs
Yeh_et_al_WikiWalk_Random_walks_on_Wikipedia_for_Semantic_Relatedness	Personalizing PageRank for Word Sense Disambiguation [10]	nnori
Yano_et_al_NAACL_2009	Link-PLSA-LDA: A new unsupervised model for topics and influence of blogs [11]	kwmurray
Ramage_et_al_ICWSM_2010	Is it Really About Me? Message Content in Social Awareness Streams [12]	yuchenz	Compare_Ramage_Naaman
Rodriguez_et_al_Oct_2011	The origin of bursts and heavy tails in human dynamics [13]	dzheng	Compare_Rodriguez_Barabasi
Measuring_User_Influence_in_Twitter:_The_Million_Follower_Fallacy	Influentials, Networks, and Public Opinion Formation [14]	Lujiang	Compare_Measuring_User_Influence_in_Twitter_and_Influentials,_Networks,_and_Public_Opinion_Formation
OConnor_et._al.,_ICWSM_2010	Widespread Worry and the Stock Market [15]	Gmontane	Comparison: O'Connor et al. ICWSM 2010 & Widespread Worry and Stock Market
Link_propagation:_A_fast_semi-supervised_learning_algorithm_for_link_prediction	Fast and scalable algorithms for semi-supervised link prediction on static and dynamic graphs [16]	epapalex	Compare Link Propagation Papers
Mrinmaya_et._al._WWW'12	The Author-Recipient-Topic Model for Topic and Role Discovery in Social Networks: Experiments with Enron and Academic Email [17]	Norii	Comparison_Mrinmaya_et._al._WWW2012_and_McCallum_et_al_2004
Yano_et_al_ICWSM_2010._What’s_Worthy_of_Comment?_Content_and_Comment_Volume_in_Political_Blogs	Mixed membership models of scientific publication [18]	ymiao	Comparison mixed membership topic poisson
Rosen-Zvi_et_al,_The_Author-Topic_Model_for_Authors_and_Documents	The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity [19]	rgkulkar	http://malt.ml.cmu.edu/mw/index.php/Comparison_Rosen-Zvi_el_al_and_cohn_et_al
Reviewing_social_media_use_by_clinicians	Integrating the hospital library with patient care, teaching and research: model and Web 2.0 tools to create a social and collaborative community of clinical research in a hospital setting. [20]
Agarwal_et_al,_ICWSM_2009#Related_Works_and_Papers	Latent Friend Mining from Blog Data, ICDM 2006 [21]	zeyuz	Compare_latentfriend_familiarstranger
Hassan_et_al,_ICWSM_2009	Document representation and query expansion models for blog recommendation [22]	sushantk	Compare Hassan et al, ICWSM 2009 and Document representation and query expansion models for blog recommendation
E.A._Leicht,_Structure_of_Time_Evo_citation_networks_2007	Detecting Topic Evolution in Scientific Literature: How Can Citations Help? [23]	ziy	Comparison of Topic Evolution Analysis with Citations
Birke&Sarkar,FigLanguages07	A Clustering Approach for the Nearly Unsupervised Recognition of Nonliteral Language, EACL-2006 [24]	tinghaoh	Comparison of Birke07 and Birke06
A_Discriminative_Latent_Variable_Model_for_SMT	An End-to-End Discriminative Approach to Machine Translation [25]	lingwang	Comparative Study of Discriminative Models in SMT
Davidov_et_al_COLING_10	Structured Models for Fine-to-Coarse Sentiment Analysis [26]	ydalal	Comparative Study : Sentiment Analysis using Automated pattern based appraoch VS Single structured model
Anderson_et_al_KDD2012	Predicting web searcher satisfaction with existing community-based answers [27]	anikag	Comparative Study of CQA : Anderson et al and Liu et al
Leskovec_et_al.,_WWW_2010	Statistical properties of community structure in large social and information networks. In WWW ’08 [28]	zhua	Compare Leskovec et al. WWW 10 and Leskovec et al. WWW 08
Accurate_Unlexicalized_Parsing	Learning Accurate, Compact, and Interpretable Tree Annotation, S. Petrov, L. Barrett, R. Thibaux, D. Klein, ACL 2006 [29]
Esuli_and_Sebastiani_LREC_2006	Determining term subjectivity and term orientation for opinion mining. [30]	ytsvetko	Compare Esuli and Sebastiani LREC 2006 vs. Esuli and Sebastiani EACL 2006
Gilbert_et_al.,_ICWSM_2010	A Sentiment Detection Engine for Internet Stock Message Boards [31]	nloghman	Comparison: Widespread Worry and the Stock Market versus Sentiment Detection Engine for Internet Stock Message Boards
Akcora_et_al,_SOMA_2010	L. Ku, Y. Liang, and H. Chen. Opinion extraction, summarization and tracking in news and blog corpora. In Proceedings of AAAI-2006 [32]	zhouyu	Compare_Ku_Akcora#Two_Papers
Chambers_and_Jurafsky,_Unsupervised_Learning_of_Narrative_Event_Chains,_ACL_2008	Chklovski and Pantel (2004) Verbocean:Mining the web for fine-grained semantic verb relations [33]	mmahavee	http://malt.ml.cmu.edu/mw/index.php/Comparing_Unsupervised_Learning_of_Narrative_Event_Chains_and_Mining_the_web_for_fine-grained_semantic_verb_relations
BinLu_et_al._ACL2011	Learning Multilingual Subjective Language via Cross-Lingual Projections [34]	lingpenk	Compare_BinLu_Rada_Two_Papers
Domain-Assisted_Product_Aspect_Hierarchy_Generation:_Towards_Hierarchical_Organization_of_Unstructured_Consumer_Reviews	Learning object models from semistructured Web documents [35]
A_Latent_Variable_Model_for_Geographic_Lexical_Variation	Q. Mei, C. Liu, H. Su, and C. X Zhai. 2006. A probabilistic approach to spatiotemporal theme pattern mining on weblogs. In Proceedings of WWW [36]	lanzhzh	Comparison: A_Latent_Variable_Model_for_Geographic_Lexical_Variation and A probabilistic approach to spatiotemporal theme pattern mining on weblogs
Collier_et_al._Journal_of_Biomedical_Semantics_2011	Modeling Spread of Disease from Social Interaction [37]	rajarshd	Comparison: Collier et al. Journal of Biomedical Semantics 2011 and Sadilek et al Sixth AAAI International Conference on Weblogs and Social Media (ICWSM)
Capturing_Global_Mood_Levels_using_Blog_Posts	Modeling Public Mood and Emotion: Twitter Sentiment and Socio-Economic Phenomena [38]	yubink	Bollen 2011 vs Mishne 2006
Andreevskaia_et_al.,_ICWSM_2007	M. Hurst and K. Nigam. Retrieving topical sentiments from online document collection. [39]	srawat	Comparitive Study
Das_Sarma_et._al.,_Dynamic_Relationship_and_Event_Discovery,_WSDM_2011	Q. Zhao, P. Mitra, and B. Chen. Temporal and information flow based event detection from social text streams. In AAAI, 2007 [40]	ysim	Paper comparison