BibSLEIGH
BibSLEIGH corpus
BibSLEIGH tags
BibSLEIGH bundles
BibSLEIGH people
CC-BY
Open Knowledge
XHTML 1.0 W3C Rec
CSS 2.1 W3C CanRec
email twitter
Used together with:
analysi (57)
classif (25)
base (24)
model (21)
use (20)

Stem sentiment$ (all stems)

127 papers:

HTHT-2015-GutierrezP #microblog #sentiment
Sentiment-based User Profiles in Microblogging Platforms (FJG, BP), pp. 23–32.
HTHT-2015-MishraDBS #analysis #incremental #learning #sentiment
Sentiment Analysis with Incremental Human-in-the-Loop Learning and Lexical Resource Customization (SM, JD, JB, ES), pp. 323–325.
ICSMEICSME-2015-JongelingDS #analysis #re-engineering #research #sentiment #tool support
Choosing your weapons: On sentiment analysis tools for software engineering research (RJ, SD, AS), pp. 531–535.
HCIHIMI-IKD-2015-GonzalezCB #approach #design #modelling #sentiment
Modeling User’s Sentiment in User Segmentations: An Argumentation Approach for User Centered Design (MPG, CIC, RFB), pp. 595–606.
HCISCSM-2015-KinclNPS #analysis #independence #sentiment
Language-Independent Sentiment Analysis with Surrounding Context Extension (TK, MN, JP, PS), pp. 158–168.
ECIRECIR-2015-CanneytCD #classification #sentiment #topic #twitter
Topic-Dependent Sentiment Classification on Twitter (SVC, NC, BD), pp. 441–446.
ECIRECIR-2015-HagenPBS #classification #detection #sentiment #twitter #using
Twitter Sentiment Detection via Ensemble Classification Using Averaged Confidence Scores (MH, MP, MB, BS), pp. 741–754.
ECIRECIR-2015-HuynhHR #analysis #learning #sentiment #strict
Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis (TH, YH, SMR), pp. 447–452.
ECIRECIR-2015-LeeL #sentiment
Measuring User Influence, Susceptibility and Cynicalness in Sentiment Diffusion (RKWL, EPL), pp. 411–422.
ECIRECIR-2015-Moghaddam #analysis #fault #feedback #mining #sentiment
Beyond Sentiment Analysis: Mining Defects and Improvements from Customer Feedback (SM), pp. 400–410.
ECIRECIR-2015-Peleja #graph #named #sentiment
PopMeter: Linked-Entities in a Sentiment Graph (FP), pp. 785–788.
ECIRECIR-2015-PelejaM #learning #retrieval #sentiment
Learning Sentiment Based Ranked-Lexicons for Opinion Retrieval (FP, JM), pp. 435–440.
MLDMMLDM-2015-CoralloFMACCGS #analysis #approach #sentiment
Sentiment Analysis for Government: An Optimized Approach (AC, LF, MM, MA, AC, VC, EG, DS), pp. 98–112.
MLDMMLDM-2015-ShaluntsB #analysis #named #sentiment
SentiSAIL: Sentiment Analysis in English, German and Russian (GS, GB), pp. 87–97.
SIGIRSIGIR-2015-SeverynM15a #analysis #network #sentiment #twitter
Twitter Sentiment Analysis with Deep Convolutional Neural Networks (AS, AM), pp. 959–962.
SIGIRSIGIR-2015-YangKML #modelling #parametricity #sentiment #topic
Parametric and Non-parametric User-aware Sentiment Topic Models (ZY, AK, AM, SL), pp. 413–422.
SACSAC-2015-DAddioM #approach #collaboration #sentiment
A sentiment-based item description approach for kNN collaborative filtering (RMD, MGM), pp. 1060–1065.
SACSAC-2015-DermoucheKVL #modelling #sentiment #topic
A joint model for topic-sentiment modeling from text (MD, LK, JV, SL), pp. 819–824.
SACSAC-2015-IqbalKK #analysis #sentiment
Bias-aware lexicon-based sentiment analysis (MI, AK, FK), pp. 845–850.
SIGMODSIGMOD-2014-ZhuGCL #analysis #clustering #graph #sentiment #social #social media
Tripartite graph clustering for dynamic sentiment analysis on social media (LZ, AG, JC, KL), pp. 1531–1542.
MSRMSR-2014-GuzmanAL #analysis #commit #empirical #git #sentiment
Sentiment analysis of commit comments in GitHub: an empirical study (EG, DA, YL), pp. 352–355.
MSRMSR-2014-PleteaVS #analysis #git #security #sentiment
Security and emotion: sentiment analysis of security discussions on GitHub (DP, BV, AS), pp. 348–351.
EDOCEDOC-2014-MukkamalaHV #analysis #sentiment #social
Fuzzy-Set Based Sentiment Analysis of Big Social Data (RRM, AH, RKV), pp. 71–80.
CIKMCIKM-2014-FangQHZ #bibliography #composition #ranking #sentiment #summary #using
Ranking Sentiment Explanations for Review Summarization Using Dual Decomposition (LF, QQ, MH, XZ), pp. 1931–1934.
CIKMCIKM-2014-LiangZHGB #identification #named #novel #sentiment #word
CONR: A Novel Method for Sentiment Word Identification (JL, XZ, YH, LG, SB), pp. 1943–1946.
CIKMCIKM-2014-LimB #sentiment #topic #twitter
Twitter Opinion Topic Model: Extracting Product Opinions from Tweets by Leveraging Hashtags and Sentiment Lexicon (KWL, WLB), pp. 1319–1328.
CIKMCIKM-2014-LinJXWCW #analysis #sentiment
A Cross-Lingual Joint Aspect/Sentiment Model for Sentiment Analysis (ZL, XJ, XX, WW, XC, YW), pp. 1089–1098.
CIKMCIKM-2014-LinLYC #classification #modelling #sentiment
Exploring Ensemble of Models in Taxonomy-based Cross-Domain Sentiment Classification (CKL, YYL, CHY, HHC), pp. 1279–1288.
ECIRECIR-2014-MonizJ #analysis #sentiment
Sentiment Analysis and the Impact of Employee Satisfaction on Firm Earnings (AM, FdJ), pp. 519–527.
KDDKDD-2014-DiaoQWSJW #aspect-oriented #modelling #recommendation #sentiment
Jointly modeling aspects, ratings and sentiments for movie recommendation (JMARS) (QD, MQ, CYW, AJS, JJ, CW), pp. 193–202.
KDDKDD-2014-SudhofEMP #sentiment #social
Sentiment expression conditioned by affective transitions and social forces (MS, AGE, ALM, CP), pp. 1136–1145.
KDIRKDIR-2014-HasnaMDP #recommendation #sentiment
Sentiment Polarity Extension for Context-Sensitive Recommender Systems (OLH, FCM, MD, RP), pp. 126–137.
KDIRKDIR-2014-LiuF #analysis #classification #sentiment #topic #web
Web Content Classification based on Topic and Sentiment Analysis of Text (SL, TF), pp. 300–307.
KDIRKDIR-2014-LiuF14a #analysis #classification #n-gram #sentiment #similarity #web
Combining N-gram based Similarity Analysis with Sentiment Analysis in Web Content Classification (SL, TF), pp. 530–537.
KDIRKDIR-2014-NagwanshiM #detection #semantics #sentiment #using
Sarcasm Detection using Sentiment and Semantic Features (PN, CEVM), pp. 418–424.
KDIRKDIR-2014-PsomakelisTAV #analysis #sentiment #twitter
Comparing Methods for Twitter Sentiment Analysis (EP, KT, DA, TAV), pp. 225–232.
KDIRKDIR-2014-WanJLL #analysis #challenge #sentiment #web
Sentimental Analysis of Web Financial Reviews — Opportunities and Challenges (CW, TJ, DL, GL), pp. 366–373.
KMISKMIS-2014-DinsoreanuB #classification #sentiment #twitter
Unsupervised Twitter Sentiment Classification (MD, AB), pp. 220–227.
RecSysRecSys-2014-YuanMZS #predict #sentiment
Exploiting sentiment homophily for link prediction (GY, PKM, ZZ, MPS), pp. 17–24.
SIGIRSIGIR-2014-HaiCCLC #bibliography #sentiment
Coarse-to-fine review selection via supervised joint aspect and sentiment model (ZH, GC, KC, WL, PC), pp. 617–626.
SIGIRSIGIR-2014-LourencoVPMFP #analysis #sentiment
Economically-efficient sentiment stream analysis (RLdOJ, AV, AMP, WMJ, RF, SP), pp. 637–646.
SIGIRSIGIR-2014-PelejaSM #analysis #sentiment
Reputation analysis with a ranked sentiment-lexicon (FP, JS, JM), pp. 1207–1210.
SIGIRSIGIR-2014-ZhangL0ZLM #analysis #modelling #recommendation #sentiment
Explicit factor models for explainable recommendation based on phrase-level sentiment analysis (YZ, GL, MZ, YZ, YL, SM), pp. 83–92.
SIGIRSIGIR-2014-ZhangZ0LM #bibliography #classification #sentiment
Do users rate or review?: boost phrase-level sentiment labeling with review-level sentiment classification (YZ, HZ, MZ, YL, SM), pp. 1027–1030.
RERE-2014-GuzmanM #analysis #fine-grained #how #sentiment
How Do Users Like This Feature? A Fine Grained Sentiment Analysis of App Reviews (EG, WM), pp. 153–162.
HTHT-2013-KrestelS #generative #sentiment #topic
Generating contextualized sentiment lexica based on latent topics and user ratings (RK, SS), pp. 129–138.
HTHT-2013-YangZYW #personalisation #recommendation #sentiment
A sentiment-enhanced personalized location recommendation system (DY, DZ, ZY, ZW), pp. 119–128.
ICDARICDAR-2013-NalisnickB #network #sentiment
Extracting Sentiment Networks from Shakespeare’s Plays (ETN, HSB), pp. 758–762.
SIGMODSIGMOD-2013-TsytsarauAP #correlation #performance #scalability #sentiment
Efficient sentiment correlation for large-scale demographics (MT, SAY, TP), pp. 253–264.
HCIHCI-III-2013-DasG #exclamation #sentiment
Sentimental Eyes! (AD, BG), pp. 310–318.
HCIHIMI-D-2013-YanagimotoSY #classification #estimation #network #sentiment #using #word
Word Classification for Sentiment Polarity Estimation Using Neural Network (HY, MS, AY), pp. 669–677.
HCIOCSC-2013-YuanOXS #bibliography #classification #sentiment #using #web
Sentiment Classification of Web Review Using Association Rules (MY, YO, ZX, HS), pp. 442–450.
CIKMCIKM-2013-BrossE #automation #bibliography #mining #sentiment
Automatic construction of domain and aspect specific sentiment lexicons for customer review mining (JB, HE), pp. 1077–1086.
CIKMCIKM-2013-FangHZ #analysis #bibliography #sentiment
Exploring weakly supervised latent sentiment explanations for aspect-level review analysis (LF, MH, XZ), pp. 1057–1066.
ECIRECIR-2013-ErmakovE #classification #sentiment
Sentiment Classification Based on Phonetic Characteristics (SE, LE), pp. 706–709.
KDIRKDIR-KMIS-2013-CheetiSC #adaptation #approach #classification #naive bayes #sentiment #syntax #using
Cross-domain Sentiment Classification using an Adapted Naïve Bayes Approach and Features Derived from Syntax Trees (SC, AS, DC), pp. 169–176.
KDIRKDIR-KMIS-2013-DimasKV #approach #sentiment #twitter
Every Character Counts — A Character based Approach to Determine Political Sentiment on Twitter (AD, PCK, EMV), pp. 261–266.
KDIRKDIR-KMIS-2013-LlavoriLGNAS #analysis #framework #named #sentiment #towards
i-SLOD: Towards an Infrastructure for Enabling the Dissemination and Analysis of Sentiment Data (RBL, DML, LGM, VN, MJA, IS), pp. 214–219.
RecSysRecSys-2013-DongOSMS #recommendation #sentiment
Sentimental product recommendation (RD, MPO, MS, KM, BS), pp. 411–414.
SIGIRSIGIR-2013-AktolgaA #bias #sentiment
Sentiment diversification with different biases (EA, JA), pp. 593–602.
SIGIRSIGIR-2013-PappasP #analysis #collaboration #sentiment
Sentiment analysis of user comments for one-class collaborative filtering over ted talks (NP, APB), pp. 773–776.
SACSAC-2013-HogenboomBFBJK #analysis #sentiment
Exploiting emoticons in sentiment analysis (AH, DB, FF, MB, FdJ, UK), pp. 703–710.
HTHT-2012-AisoposPTV #analysis #comparative #microblog #sentiment
Content vs. context for sentiment analysis: a comparative analysis over microblogs (FA, GP, KT, TAV), pp. 187–196.
CHICHI-2012-YangAAWL #sentiment
The way i talk to you: sentiment expression in an organizational context (JY, LAA, MSA, ZW, CYL), pp. 551–554.
CIKMCIKM-2012-AmiriC #mining #sentiment
Mining sentiment terminology through time (HA, TSC), pp. 2060–2064.
CIKMCIKM-2012-JuLSZHL #classification #documentation #sentiment #word
Dual word and document seed selection for semi-supervised sentiment classification (SJ, SL, YS, GZ, YH, XL), pp. 2295–2298.
CIKMCIKM-2012-LinTCXS #effectiveness #performance #sentiment #using
Effective and efficient?: bilingual sentiment lexicon extraction using collocation alignment (ZL, ST, XC, XX, WS), pp. 1542–1546.
CIKMCIKM-2012-MukherjeeMRB #multi #named #sentiment #twitter
TwiSent: a multistage system for analyzing sentiment in twitter (SM, AM, BAR, PB), pp. 2531–2534.
CIKMCIKM-2012-VuralCS #crawling #sentiment #web
Sentiment-focused web crawling (AGV, BBC, PS), pp. 2020–2024.
CIKMCIKM-2012-XuTLCL #aspect-oriented #sentiment #towards
Towards jointly extracting aspects and aspect-specific sentiment knowledge (XX, ST, YL, XC, ZL), pp. 1895–1899.
ECIRECIR-2012-Garcia-MoyaAL #modelling #probability #retrieval #sentiment
Combining Probabilistic Language Models for Aspect-Based Sentiment Retrieval (LGM, HAS, RBL), pp. 561–564.
ECIRECIR-2012-KarlgrenSOEH #analysis #sentiment
Usefulness of Sentiment Analysis (JK, MS, FO, FE, OH), pp. 426–435.
KDDKDD-2012-ZhaoDWX #analysis #named #sentiment #twitter
MoodLens: an emoticon-based sentiment analysis system for chinese tweets (JZ, LD, JW, KX), pp. 1528–1531.
KDIRKDIR-2012-FukumotoMM #analysis #collaboration #recommendation #sentiment
Collaborative Filtering based on Sentiment Analysis of Guest Reviews for Hotel Recommendation (FF, CM, SM), pp. 193–198.
KDIRKDIR-2012-MountassirBB #analysis #problem #semistructured data #sentiment #set
Addressing the Problem of Unbalanced Data Sets in Sentiment Analysis (AM, HB, IB), pp. 306–311.
SEKESEKE-2012-JangidPE #analysis #mobile #predict #sentiment #using
A Mobile Application for Stock Market Prediction Using Sentiment Analysis (KJ, PP, ME), pp. 13–18.
SIGIRSIGIR-2012-ONeil #ranking #sentiment #using
Entity sentiment extraction using text ranking (JO), p. 1024.
SIGIRSIGIR-2012-ZhangXCHDALC #identification #information management #semantics #sentiment #syntax
Sentiment identification by incorporating syntax, semantics and context information (KZ, YX, YC, DH, DD, AA, WkL, ANC), pp. 1143–1144.
SACSAC-2012-Kawamae #sentiment
Joint sentiment aspect model (NK), pp. 205–210.
SACSAC-2012-KhucSRR #analysis #distributed #scalability #sentiment #towards #twitter
Towards building large-scale distributed systems for twitter sentiment analysis (VNK, CS, RR, JR), pp. 459–464.
CSCWCSCW-2011-ParkKKLS #predict #sentiment
The politics of comments: predicting political orientation of news stories with commenters’ sentiment patterns (SP, MK, JK, YL, JS), pp. 113–122.
CIKMCIKM-2011-BespalovBQS #analysis #classification #n-gram #sentiment
Sentiment classification based on supervised latent n-gram analysis (DB, BB, YQ, AS), pp. 375–382.
CIKMCIKM-2011-GaoL #adaptation #analysis #classification #probability #sentiment #using
A cross-domain adaptation method for sentiment classification using probabilistic latent analysis (SG, HL), pp. 1047–1052.
CIKMCIKM-2011-GuoZGS #analysis #aspect-oriented #multi #sentiment
Domain customization for aspect-oriented opinion analysis with multi-level latent sentiment clues (HG, HZ, ZG, ZS), pp. 2493–2496.
CIKMCIKM-2011-LauLBW #learning #scalability #sentiment #web
Leveraging web 2.0 data for scalable semi-supervised learning of domain-specific sentiment lexicons (RYKL, CLL, PB, KFW), pp. 2457–2460.
CIKMCIKM-2011-LinTC #classification #independence #sentiment #using #word
Language-independent sentiment classification using three common words (ZL, ST, XC), pp. 1041–1046.
CIKMCIKM-2011-LiuLZD #classification #network #sentiment
Sentiment classification via l2-norm deep belief network (TL, ML, SZ, XD), pp. 2489–2492.
CIKMCIKM-2011-LiZWLW #classification #sentiment
Imbalanced sentiment classification (SL, GZ, ZW, SYML, RW), pp. 2469–2472.
CIKMCIKM-2011-MohtaramiALT #nondeterminism #predict #sentiment
Predicting the uncertainty of sentiment adjectives in indirect answers (MM, HA, ML, CLT), pp. 2485–2488.
CIKMCIKM-2011-PeraQN #multi #sentiment
A query-based multi-document sentiment summarizer (MSP, RQ, YKN), pp. 1071–1076.
CIKMCIKM-2011-WangWLZZ #analysis #approach #classification #graph #hashtag #sentiment #topic #twitter
Topic sentiment analysis in twitter: a graph-based hashtag sentiment classification approach (XW, FW, XL, MZ, MZ), pp. 1031–1040.
CIKMCIKM-2011-WeichselbraunGS #game studies #sentiment #using
Using games with a purpose and bootstrapping to create domain-specific sentiment lexicons (AW, SG, AS), pp. 1053–1060.
ECIRECIR-2011-Carrillo-de-AlbornozPGD #analysis #bibliography #mining #rating #sentiment
A Joint Model of Feature Mining and Sentiment Analysis for Product Review Rating (JCdA, LP, PG, AD), pp. 55–66.
ECIRECIR-2011-Demartini #named #retrieval #sentiment
ARES: A Retrieval Engine Based on Sentiments — Sentiment-Based Search Result Annotation and Diversification (GD), pp. 772–775.
ECIRECIR-2011-He #classification #sentiment
Latent Sentiment Model for Weakly-Supervised Cross-Lingual Sentiment Classification (YH), pp. 214–225.
ECIRECIR-2011-TackstromM #fine-grained #modelling #predict #sentiment
Discovering Fine-Grained Sentiment with Latent Variable Structured Prediction Models (OT, RTM), pp. 368–374.
ICMLICML-2011-GlorotBB #adaptation #approach #classification #learning #scalability #sentiment
Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach (XG, AB, YB), pp. 513–520.
KDDKDD-2011-GuerraVMA #analysis #approach #bias #realtime #sentiment
From bias to opinion: a transfer-learning approach to real-time sentiment analysis (PHCG, AV, WMJ, VA), pp. 150–158.
KDDKDD-2011-TanLTJZL #analysis #network #sentiment #social
User-level sentiment analysis incorporating social networks (CT, LL, JT, LJ, MZ, PL), pp. 1397–1405.
MLDMMLDM-2011-JiangMY #analysis #sentiment #topic
Topic Sentiment Change Analysis (YJ, WM, CTY), pp. 443–457.
RecSysRecSys-2011-Faridani #analysis #canonical #correlation #recommendation #sentiment #using
Using canonical correlation analysis for generalized sentiment analysis, product recommendation and search (SF), pp. 355–358.
SIGIRSIGIR-2011-SilvaGVMF #analysis #effectiveness #self #sentiment
Effective sentiment stream analysis with self-augmenting training and demand-driven projection (ISS, JG, AV, WMJ, RF), pp. 475–484.
CHICHI-2010-DiakopoulosS #performance #sentiment #twitter
Characterizing debate performance via aggregated twitter sentiment (ND, DAS), pp. 1195–1198.
CIKMCIKM-2010-BerminghamS #microblog #question #sentiment
Classifying sentiment in microblogs: is brevity an advantage? (AB, AFS), pp. 1833–1836.
CIKMCIKM-2010-DragutYSM #sentiment #taxonomy #word
Construction of a sentimental word dictionary (ECD, CTY, APS, WM), pp. 1761–1764.
CIKMCIKM-2010-He #classification #learning #sentiment
Learning sentiment classification model from labeled features (YH), pp. 1685–1688.
ICPRICPR-2010-LiZXCG #analysis #documentation #multi #sentiment
Exploiting Combined Multi-level Model for Document Sentiment Analysis (SL, HZ, WX, GC, JG), pp. 4141–4144.
KDIRKDIR-2010-LieglGSH #automation #detection #sentiment #taxonomy
Dictionary Extension for Improving Automated Sentiment Detection (JL, SG, AS, AHH), pp. 404–407.
SIGIRSIGIR-2010-LeeLSR #precise #retrieval #sentiment #using
High precision opinion retrieval using sentiment-relevance flows (SWL, JTL, YIS, HCR), pp. 817–818.
SIGIRSIGIR-2010-LiuYHA #adaptation #analysis #performance #predict #sentiment
S-PLASA+: adaptive sentiment analysis with application to sales performance prediction (YL, XY, XH, AA), pp. 873–874.
CIKMCIKM-2009-DuT #sentiment
Building domain-oriented sentiment lexicon by improved information bottleneck (WD, ST), pp. 1749–1752.
CIKMCIKM-2009-JiaYM #analysis #effectiveness #retrieval #sentiment
The effect of negation on sentiment analysis and retrieval effectiveness (LJ, CTY, WM), pp. 1827–1830.
CIKMCIKM-2009-LinH #analysis #sentiment #topic
Joint sentiment/topic model for sentiment analysis (CL, YH), pp. 375–384.
CIKMCIKM-2009-LiuZ #classification #sentiment #using
Cross-domain sentiment classification using a two-stage method (KL, JZ), pp. 1717–1720.
CIKMCIKM-2009-QiuZHZ #classification #named #self #sentiment
SELC: a self-supervised model for sentiment classification (LQ, WZ, CH, KZ), pp. 929–936.
ECIRECIR-2009-FanC #sentiment
Sentiment-Oriented Contextual Advertising (TKF, CHC), pp. 202–215.
ECIRECIR-2009-NaLNL #retrieval #sentiment
Improving Opinion Retrieval Based on Query-Specific Sentiment Lexicon (SHN, YL, SHN, JHL), pp. 734–738.
ECIRECIR-2009-TanCWX #adaptation #analysis #naive bayes #sentiment
Adapting Naive Bayes to Domain Adaptation for Sentiment Analysis (ST, XC, YW, HX), pp. 337–349.
KDDKDD-2009-MelvilleGL #analysis #classification #sentiment
Sentiment analysis of blogs by combining lexical knowledge with text classification (PM, WG, RDL), pp. 1275–1284.
SIGIRSIGIR-2009-LiSDZ #classification #sentiment
Knowledge transformation for cross-domain sentiment classification (TL, VS, CHQD, YZ), pp. 716–717.
SIGIRSIGIR-2008-TanWC #detection #sentiment #using
Combining learn-based and lexicon-based techniques for sentiment detection without using labeled examples (ST, YW, XC), pp. 743–744.
SIGIRSIGIR-2008-ZhangY #generative #retrieval #sentiment #topic
A generation model to unify topic relevance and lexicon-based sentiment for opinion retrieval (MZ, XY), pp. 411–418.
CIKMCIKM-2007-TanWTC #analysis #novel #problem #sentiment
A novel scheme for domain-transfer problem in the context of sentiment analysis (ST, GW, HT, XC), pp. 979–982.
ECIRECIR-2007-MeenaP #analysis #sentiment #using
Sentence Level Sentiment Analysis in the Presence of Conjuncts Using Linguistic Analysis (AM, TVP), pp. 573–580.
SIGIRSIGIR-2007-LiuHAY #named #performance #predict #sentiment #using
ARSA: a sentiment-aware model for predicting sales performance using blogs (YL, XH, AA, XY), pp. 607–614.
CIKMCIKM-2005-WhitelawGA #analysis #sentiment #using
Using appraisal groups for sentiment analysis (CW, NG, SA), pp. 625–631.
DRRDRR-2004-HurstN #documentation #online #sentiment #topic
Retrieving topical sentiments from online document collections (MFH, KN), pp. 27–34.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
Hosted as a part of SLEBOK on GitHub.