Predicting the Future with Social Media

Opinion Mining and Sentiment Analysis

Pang, B., & Lee, L. (2008) · now publishers, Inc. eBooks · doi:10.1561/9781601981516 · Cited by 6,957

Opinion mining and sentiment analysis

Pang, B., & Lee, L. (2008) · Foundations and Trends® in Information Retrieval · doi:10.1561/1500000011 · Cited by 6,372

Why we twitter

Java, A., Song, X., Finin, T., & Tseng, B. L. (2007) · doi:10.1145/1348549.1348556 · Cited by 2,662

Cheap and fast---but is it good?: evaluating non-expert annotations for natural language tasks

Snow, R., O'Connor, B., Jurafsky, D., & Ng, A. Y. (2008) · Proceedings of the Conference on Empirical Methods in Natural Language Processing - EMNLP '08 · doi:10.3115/1613715.1613751 · Cited by 1,887

Twitter power: Tweets as electronic word of mouth

Jansen, B. J. J., Zhang, M., Sobel, K., & Chowdury, A. (2009) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.21149 · Cited by 1,766

Social networks that matter: Twitter under the microscope

Huberman, B. A., Romero, D. M., & Wu, F. (2008) · First Monday · doi:10.5210/fm.v14i1.2317 · Cited by 965

Large-Scale Sentiment Analysis for News and Blogs

Godbole, N., Srinivasaiah, M., & Skiena, S. (2007) · International Conference on Weblogs and Social Media · Cited by 581

The predictive power of online chatter

Gruhl, D., Guha, R. V., Kumar, R., Novak, J., & Tomkins, A. (2005) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/1081870.1081883 · Cited by 411

The dynamics of viral marketing

Leskovec, J., Adamic, L. A., & Huberman, B. A. (2006) · ACM Conference on Electronic Commerce (EC) · doi:10.1145/1134707.1134732 · Cited by 391

Predicting Movie Sales from Blogger Sentiment

Mishne, G., & Glance, N. (2006) · Cited by 354

Big Social Data Analytics for Public Health: Predicting Facebook Post Performance Using Artificial Neural Networks and Deep Learning

Straton, N., Mukkamala, R. R., & Vatrapu, R. (2017) · IEEE International Congress on Big Data (BigData Congress) · doi:10.1109/bigdatacongress.2017.21 · Cited by 17

Predicting IMDb Ratings of Pre-release Movies with Factorization Machines Using Social Media

Cizmeci, B., & Öğüdücü, Ş. G. (2018) · doi:10.1109/ubmk.2018.8566661 · Cited by 17

Utilizing Social Media Data for Psychoanalysis to Study Human Personality

Emmert‐Streib, F., Yli-Harja, O. P., & Dehmer, M. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.02596 · Cited by 17

Kurumsal İletişimde Diyalojik Sosyal Medya Kullanımı: Vakıf ve Devlet Üniversiteleri Açısından Karşılaştırmalı Bir Değerlendirme

Yılmaz, N., & Aktaş, H. (2020) · Anadolu Üniversitesi Sosyal Bilimler Dergisi · doi:10.18037/ausbd.701827 · Cited by 17

Exploring incivility and moral foundations toward Asians in English-speaking tweets in hate crime-reporting cities during the COVID-19 pandemic

Kim, B., Cooks, E., & Kim, S.-K. (2021) · Internet Research · doi:10.1108/intr-11-2020-0678 · Cited by 17

Biocom Usp: Tweet Sentiment Analysis with Adaptive Boosting Ensemble

Silva, N., Junior, E. R. H., & Hruschka, E. R. (2014) · International Workshop on Semantic Evaluation (SemEval) · doi:10.3115/v1/s14-2017 · Cited by 16

Telegram: Data Collection, Opportunities and Challenges

Khaund, T., Hussain, M. N., Shaik, M., & Agarwal, N. (2021) · Communications in computer and information science · doi:10.1007/978-3-030-76228-5_37 · Cited by 16

Designing a forecasting assistant of the Bitcoin price based on deep learning using market sentiment analysis and multiple feature extraction

Fakharchian, S. (2023) · Soft Computing · doi:10.1007/s00500-023-09028-5 · Cited by 21

Similarity and Ties in Social Networks: a Study of the YouTube Social Network

Rad, A. A., & Benyoucef, M. (2013) · Cited by 16

Social intelligence framework: Extracting and analyzing opinions for social CRM

Ennaji, F. Z., Fazziki, A. E., Sadgal, M., & Benslimane, D. (2015) · IEEE/ACS International Conference on Computer Systems and Applications (AICCSA) · doi:10.1109/aiccsa.2015.7507229 · Cited by 15

Leveraging Social Media to Predict Continuation and Reversal in Asset Prices

Houlihan, P., & Creamer, G. G. (2019) · Computational Economics · doi:10.1007/s10614-019-09932-9 · Cited by 16

A Consumer Behavior Prediction Model Based on Multivariate Real-Time Sequence Analysis

Guo, L., Zhang, B., & Zhao, X. (2021) · Mathematical Problems in Engineering · doi:10.1155/2021/6688750 · Cited by 16

Public Health Policy Monitoring through Public Perceptions: A Case of COVID-19 Tweet Analysis

Li, C.-Y., Renda, M., Yusuf, F., Geller, J., & Chun, S. A. (2022) · Information · doi:10.3390/info13110543 · Cited by 16

The TweetBeat of the City: Microblogging Used for Discovering Behavioural Patterns during the MWC2012

Villatoro, D., Serna, J., Rodríguez, V., & Torrent‐Moreno, M. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-36074-9_5 · Cited by 16

6 The Architectonics of Language MOOCs

Read, T. M. (2014) · doi:10.2478/9783110420067.6 · Cited by 16

Sentiment Analysis of Arabic Tweets Using Semantic Resources

Alhoraibi, L., & Khan, M. B. (2016) · International Journal of Computing and Information Sciences · doi:10.21700/ijcis.2016.118 · Cited by 16

Efficient natural language pre-processing for analyzing large data sets

Belainine, B., Fonseca, A., & Sadat, F. (2016) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata.2016.7841060 · Cited by 16

Spatial Characteristics of Twitter Users—Toward the Understanding of Geosocial Media Production

Rzeszewski, M., & Beluch, Ł. (2017) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi6080236 · Cited by 17

Mitigating Online Product Rating Biases Through the Discovery of Optimistic, Pessimistic, and Realistic Reviewers

Lim, S., & Tucker, C. S. (2017) · Journal of Mechanical Design · doi:10.1115/1.4037612 · Cited by 17

A layer-wise deep stacking model for social image popularity prediction

Lin, Z., Huang, F., Li, Y., Yang, Z., & Liu, W. (2018) · World Wide Web · doi:10.1007/s11280-018-0590-1 · Cited by 15

The New Era of Business Intelligence Applications: Building from a Collaborative Point of View

Teruel, M. Á., Maté, A., Navarro, E., González, P., & Trujillo, J. C. (2019) · Business & Information Systems Engineering · doi:10.1007/s12599-019-00578-3 · Cited by 16

An Opinion Mining for Indian Premier League Using Machine Learning Techniques

Arti, Dubey, K. P., & Agrawal, S. (2019) · International Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU) · doi:10.1109/iot-siu.2019.8777472 · Cited by 16

On Modelling for Bias-Aware Sentiment Analysis and Its Impact in Twitter

Mahmood, A., Khan, H. U., & Ramzan, M. (2020) · Journal of Web Engineering · doi:10.13052/jwe1540-9589.1911 · Cited by 15

Emotion Analysis Using Multilayered Networks for Graphical Representation of Tweets

Nguyen, A., Longa, A., Luca, M., Kaul, J., & Lopez, G. (2022) · IEEE Access · doi:10.1109/access.2022.3207161 · Cited by 15

Social media engagement and cryptocurrency performance

Qureshi, K., & Zaman, T. R. (2023) · PLoS ONE · doi:10.1371/journal.pone.0284501 · Cited by 15

Social Media Usage and The Academic Performance of Filipino Junior High School Students

Dimacangun, F. E., & Guillena, J. B. (2023) · International Journal of Educational Management and Development Studies · doi:10.53378/352994 · Cited by 24

Surfacing time-critical insights from social media

Alexe, B., Hernández, M. A., Hildrum, K. W., Krishnamurthy, R., Koutrika, G., Nagarajan, M., Roitman, H., Shmueli-Scheuer, M., Stanoi, I., Venkatramani, C., et al. (2012) · ACM SIGMOD International Conference on Management of Data (SIGMOD) · doi:10.1145/2213836.2213925 · Cited by 15

Data Skills and Value of Social Media: Evidence from Large-Sample Firm Value Analysis

Hitt, L. M., Jin, F., & Wu, L. (2015) · International Conference on Information Systems · Cited by 16

Modelling Influence and Reach in Sentiment Analysis

Neves‐Silva, R., Gamito, M., Pina, P., & Campos, A. R. (2016) · Procedia CIRP · doi:10.1016/j.procir.2016.03.239 · Cited by 15

Parallel Hybrid BBO Search Method for Twitter Sentiment Analysis of Large Scale Datasets Using MapReduce

Tripathi, A. K., Sharma, K., & Bala, M. (2019) · International Journal of Information Security and Privacy · doi:10.4018/ijisp.201907010107 · Cited by 15

User-driven geolocated event detection in social media

Bendimerad, A., Plantevit, M., Robardet, C., & Amer-Yahia, S. (2019) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2019.2931340 · Cited by 15

Reshaping the urban hierarchy: patterns of information diffusion on social media

Yang, J., Tsou, M., Janowicz, K., Clarke, K., & Jankowski, P. L. (2019) · Geo-spatial Information Science · doi:10.1080/10095020.2019.1641970 · Cited by 15

Advancing social media derived information messaging and management: A multi-mode development perspective

Martin, N., Rice, J., & Arthur, D. (2019) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.10.006 · Cited by 16

A year of pandemic: Levels, changes and validity of well-being data from Twitter. Evidence from ten countries

Sarracino, F., Greyling, T., O’Connor, K. J., Peroni, C., & Rossouw, S. (2023) · PLoS ONE · doi:10.1371/journal.pone.0275028 · Cited by 22

Understanding online groups through social media

Barbier, G., Tang, L., & Liu, H. (2011) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.37 · Cited by 15

Predicting Ratings for New Movie Releases from Twitter Content

Schmit, W., & Wubben, S. (2015) · Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis (WASSA) · doi:10.18653/v1/w15-2917 · Cited by 15

A Gaussian copula regression model for movie box-office revenues prediction

Duan, J., Ding, X., & Liu, T. (2017) · Science China Information Sciences · doi:10.1007/s11432-015-0905-6 · Cited by 15

Language-independent data set annotation for machine learning-based sentiment analysis

Guthier, B., Ho, K., & Saddik, A. E. (2017) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2017.8122930 · Cited by 15

Detecting the Correlation between Sentiment and User-level as well as Text-Level Meta-data from Benchmark Corpora

Mishra, S., & Diesner, J. (2018) · ACM Conference on Hypertext and Social Media (HT) · doi:10.1145/3209542.3209562 · Cited by 15

An ensemble classification approach for prediction of user’s next location based on Twitter data

Kumar, S., & Игоревна, Н. М. (2018) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-018-1134-3 · Cited by 15

Exploitation of Social Network Data for Forecasting Garment Sales

Giri, C., Thomassey, S., & Zeng, X. (2019) · International Journal of Computational Intelligence Systems · doi:10.2991/ijcis.d.191109.001 · Cited by 15

Can Tweets Replace Polls? A U.S. Health‐Care Reform Case Study

Kim, A. E., Murphy, J., Richards, A. K., Hansen, H. M., Powell, R. J., & Haney, C. (2013) · doi:10.1002/9781118751534.ch3 · Cited by 15

Should You Target Early Trend Propagators? Evidence from TwitterPreprint

Lambrecht, A., Tucker, C. E., & Wiertz, C. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2419743 · Cited by 15

Sentiment Analysis of Twitter Data for Predicting Stock Market MovementsPreprint

Pagolu, V. S., Challa, K. N. R., Panda, G., & Majhi, B. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1610.09225 · Cited by 15

Sentiment analysis within and across social media streams

Mejova, Y. A. (2012) · doi:10.17077/etd.zze4b252 · Cited by 15

Distributed Large-Scale Data Collection in Online Social Networks

Efstathiades, H., Antoniades, D., Pallis, G., & Dikaiakos, M. D. (2016) · IEEE International Conference on Collaboration and Internet Computing (CIC) · doi:10.1109/cic.2016.056 · Cited by 14

Talk, text or tag?

Woznowski, P., Tonkin, E. L., Laskowski, P., Twomey, N., Yordanova, K., & Burrows, A. (2017) · IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) · doi:10.1109/percomw.2017.7917544 · Cited by 14

Trend tracking tools for the fashion industry: the impact of social media

Rudniy, A., Rudna, O., & Park, A. (2023) · Journal of Fashion Marketing and Management · doi:10.1108/jfmm-08-2023-0215 · Cited by 14

Impact of social media posts’ characteristics on movie performance prior to release: an explainable machine learning approach

Abdulrashid, I., Ahmad, I. S., Musa, A., & Khalafalla, M. (2024) · Electronic Commerce Research · doi:10.1007/s10660-024-09852-3 · Cited by 14

Enhanced sales forecasting model using textual search data: Fusing dynamics with big data

Borah, A., & Rutz, O. J. (2024) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2024.05.007 · Cited by 14

Influence of social media on performance of movies

Shruti, Roy, S. D., & Zeng, W. (2014) · IEEE International Conference on Multimedia and Expo workshops · doi:10.1109/icmew.2014.6890664 · Cited by 14

Timely Event Detection by Networked Learners

Canzian, L., & van der Schaar, M. (2015) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2015.2389765 · Cited by 14

Sentiment Analysis on Twitter to Improve Time Series Contextual Anomaly Detection for Detecting Stock Market Manipulation

Golmohammadi, S. K., & Zai͏̈ane, O. R. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-64283-3_24 · Cited by 14

Developing a supervised learning-based social media business sentiment index

Lee, H., Lee, N., Seo, H., & Song, M. (2019) · The Journal of Supercomputing · doi:10.1007/s11227-018-02737-x · Cited by 14

INF-UFG at FiQA 2018 Task 1

Costa, D. D. F., & da Silva, N. F. F. (2018) · International World Wide Web Conference (WWW) · doi:10.1145/3184558.3191828 · Cited by 14

Tweets That Resonate: Information Flows and the Growth of Twitter's Universal Basic Income Discussion Space

Hemsley, J., García‐Murillo, M., & MacInnes, I. (2018) · Policy & Internet · doi:10.1002/poi3.175 · Cited by 14

Hoax Detection System on Twitter using Feed-Forward and Back-Propagation Neural Networks Classification Method

Kencana, C. W., Setiawan, E. B., & Kurniawan, I. (2020) · Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) · doi:10.29207/resti.v4i4.2038 · Cited by 14

Deep Learning approach for text, image, and GIF multimodal sentiment analysis

Shirzad, A., Zare, H., & Teimouri, M. (2020) · International Conference on Computer and Knowledge Engineering · doi:10.1109/iccke50421.2020.9303676 · Cited by 15

A comprehensive review and evaluation on text predictive and entertainment systems

Hamarashid, H. K., Saeed, S., & Rashid, T. A. (2022) · Soft Computing · doi:10.1007/s00500-021-06691-4 · Cited by 14

Big Data Analytics: A Literature Review Paper

Sakshi, M. P., & Malwadkar, M. G. (2023) · International Journal of Advanced Research in Science Communication and Technology · doi:10.48175/ijarsct-8160 · Cited by 14

From A Social Influence Perspective: The Impact Of Social Media On Movie Sales

Huang, J., Boh, W. F., & Goh, K. H. (2011) · Cited by 14

Decoding, hacking, and optimizing societies: Exploring potential applications of human data analytics in sociological engineering, both internally and as offensive weapons

Maus, G. (2015) · Science and Information Conference · doi:10.1109/sai.2015.7237195 · Cited by 14

Google searches and twitter mood: nowcasting telecom sales performance

Bughin, J. (2015) · NETNOMICS Economic Research and Electronic Networking · doi:10.1007/s11066-015-9096-5 · Cited by 15

A generalized Bass model for predicting the sales patterns of motion pictures having seasonality and herd behavior

Lee, Y., Kim, S., & Cha, K. C. (2012) · Journal of Global Scholars of Marketing Science · doi:10.1080/21639159.2012.721214 · Cited by 14

Comparing Print Coverage and Tweets in Elections

Murthy, D., & Petto, L. R. (2014) · Social Science Computer Review · doi:10.1177/0894439314541925 · Cited by 14

Analyzing spatiotemporal trends in social media data via smoothing spline analysis of variance

Helwig, N. E., Gao, Y., Wang, S., & Ma, P. (2015) · Spatial Statistics · doi:10.1016/j.spasta.2015.09.002 · Cited by 14

Sociopedia: An Interactive System for Event Detection and Trend Analysis for Twitter Data

Kaushik, R., Chandra, S. A., Mallya, D., Chaitanya, J. N. V. K., & Kamath, S. S. (2015) · Smart innovation, systems and technologies · doi:10.1007/978-81-322-2529-4_6 · Cited by 14

Who caught a cold ? - Identifying the subject of a symptom

Kanouchi, S., Komachi, M., Okazaki, N., Aramaki, E., & Ishikawa, H. (2015) · doi:10.3115/v1/p15-1160 · Cited by 14

Analyzing, classifying, and interpreting emotions in software users' tweets

Williams, G., & Mahmoud, A. (2017) · doi:10.5555/3105556.3105558 · Cited by 14

Challenges in the Analysis of Online Social Networks: A Data Collection Tool Perspective

Goswami, A., & Kumar, A. (2017) · Wireless Personal Communications · doi:10.1007/s11277-017-4712-3 · Cited by 14

Polarized, Together: Comparing Partisan Support for Trump’s Tweets Using Survey and Platform-Based Measures

Joseph, K., Swire‐Thompson, B., Masuga, H., Baum, M., & Lazer, D. M. J. (2019) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v13i01.3230 · Cited by 13

Using Twitter to Predict Chart Position for Songs

Tsiara, E., & Tjortjis, C. (2020) · IFIP advances in information and communication technology · doi:10.1007/978-3-030-49161-1_6 · Cited by 14

Using idiolects and sociolects to improve word prediction

Stoop, W., & van den Bosch, A. P. J. (2014) · Conference of the European Chapter of the Association for Computational Linguistics · doi:10.3115/v1/e14-1034 · Cited by 14

Emotion and sentiment in social and expressive media: Introduction to the special issue

Rosso, P., Bosco, C., Damiano, R., Patti, V., & Cambria, E. (2015) · Information Processing & Management · doi:10.1016/j.ipm.2015.11.002 · Cited by 15

Public discourse and news consumption on online social media: A quantitative, cross-platform analysis of the Italian Referendum

Vicario, M. D., Gaito, S., Quattrociocchi, W., Zignani, M., & Zollo, F. (2017) · IMT Institutional Repository (IMT School for Advanced Studies Lucca) · doi:10.48550/arxiv.1702.06016 · Cited by 28

On Predicting Election Results using Twitter and Linked Open Data: The Case of the UK 2010 Election

Karamanou, A., Tambouris, E., Kalampokis, E., & Tarabanis, K. A. (2020) · TUGraz OPEN Library (Graz University of Technology) · doi:10.3217/jucs-023-03-0280 · Cited by 14

Altmetrics (Chapter from Beyond Bibliometrics: Harnessing Multidimensional Indicators of Scholarly Impact)Preprint

Priem, J. R. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1507.01328 · Cited by 17

Marketing Education Renaissance Through Big Data Curriculum: Developing Marketing Expertise Using AI Large Language Models

Sood, S. C., & Pattinson, H. M. (2023) · International Journal of Innovation and Economic Development · doi:10.18775/ijied.1849-7551-7020.2015.86.2003 · Cited by 13

New energy vehicle demand forecasting via an improved Bass model with perceived quality identified from online reviews

Bian, Y., Shan, D., Yan, X., & Zhang, J. (2024) · Annals of Operations Research · doi:10.1007/s10479-024-06255-3 · Cited by 13

Prospects and challenges for social media in Pakistan

Memon, S. A., Mahar, S., Dhomeja, L. D., & Pirzado, F. A. (2015) · International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA) · doi:10.1109/cybersa.2015.7166124 · Cited by 13

Experiments with artificially generated noise for cleansing noisy text

Gadde, P. H., Goutam, R., Shah, R., Bayyarapu, H. S., & Subramaniam, L. V. (2011) · doi:10.1145/2034617.2034622 · Cited by 13

Revenue Prediction of Music Concerts Using the Mathematical Model of Hit Phenomena

Kawahata, Y., Genda, E., & Ishii, A. (2013) · International Conference on Biometrics and Kansei Engineering (ICBAKE) · doi:10.1109/icbake.2013.41 · Cited by 13

Associative topic models with numerical time series

Park, S., Lee, W., & Moon, I. (2015) · Information Processing & Management · doi:10.1016/j.ipm.2015.06.007 · Cited by 13

The Power of Micro-Blogging: How to Use Twitter for Predicting the Stock Market

Corea, F., & Cervellati, E. M. (2015) · Eurasian Journal of Economics and Finance · doi:10.15604/ejef.2015.03.04.001 · Cited by 13

Analyzing Public Emotion and Predicting Stock Market Using Social Media

Arafat, J., Habib, M. A., & Hossain, R. (2013) · Cited by 13

The Untold Story of USA Presidential Elections in 2016 - Insights from Twitter Analytics

Grover, P., Kar, A. K., Dwivedi, Y. K., & Janssen, M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-68557-1_30 · Cited by 13

Data Analytics Applications for Streaming Data From Social Media: What to Predict?

Emmert‐Streib, F., Yli-Harja, O. P., & Dehmer, M. (2018) · Frontiers in Big Data · doi:10.3389/fdata.2018.00002 · Cited by 14

Deep Candlestick Predictor: A Framework toward Forecasting the Price Movement from Candlestick Charts

Guo, S.-J., Hsu, F., & Hung, C. (2018) · International Symposium on Parallel Architectures, Algorithms and Programming · doi:10.1109/paap.2018.00044 · Cited by 13

THE USE OF SOCIAL MEDIA (SM) AMONG PUPILS IN A RURAL PRIMARY SCHOOL IN SARAWAK, MALAYSIA

Bayuong, P. D., Yunus, M. M., & Suliman, A. (2019) · Humanities & Social Sciences Reviews · doi:10.18510/hssr.2019.75166 · Cited by 13

The Changes of Media Landscape in Malaysia: How Citizen Journalism Poses Threats to Traditional Media

Sarawak, U. M., Taibi, M., Teh, Y. N., & Sarawak, U. M. (2020) · Jurnal Komunikasi Malaysian Journal of Communication · doi:10.17576/jkmjc-2020-3601-21 · Cited by 13

A General Purpose Model for Future Prediction Based on Web Search Data: Predicting Greek and Spanish Election

Polykalas, S. E., Prezerakos, G. N., & Konidaris, A. (2013) · International Conference on Advanced Information Networking and Applications Workshops (WAINA) · doi:10.1109/waina.2013.155 · Cited by 13

Interest-driven private friend recommendation

Samanthula, B. K., & Jiang, W. (2013) · Knowledge and Information Systems · doi:10.1007/s10115-013-0699-6 · Cited by 13

Feature Selection for Twitter Classification

Ostrowski, D. A. (2014) · IEEE International Conference on Semantic Computing (ICSC) · doi:10.1109/icsc.2014.50 · Cited by 13

Marius, the giraffe

Zimmerman, C., Chen, Y., Hardt, D., & Vatrapu, R. (2014) · ACM International Conference on Collaboration Across Boundaries: Culture, Distance & Technology (CABS) · doi:10.1145/2631488.2631501 · Cited by 13

Predicting Trends in the Twitter Social Network: A Machine Learning Approach

Das, A., Roy, M., Dutta, S., Ghosh, S., & Das, A. K. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-20294-5_49 · Cited by 13

News events prediction using Markov logic networks

Dami, S., Barforoush, A. A., & Shirazi, H. M. (2016) · Journal of Information Science · doi:10.1177/0165551516673285 · Cited by 15

The workforce analyzer: group discovery among LinkedIn public profiles

Dai, K., Vilas, A. F., & Redondo, R. P. D. (2017) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-017-0484-6 · Cited by 13

Anatomy of Viral Social Media Events

Pöyry, E., Laaksonen, S.-M., Kekkonen, A., & Pääkkönen, J. (2018) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2018.272 · Cited by 15

Predicting Success of Bollywood Movies Using Machine Learning Techniques

Jaiswal, S. R., & Sharma, D. (2017) · Bangalore Annual Compute Conference · doi:10.1145/3140107.3140126 · Cited by 13

Time series clustering based on sparse subspace clustering algorithm and its application to daily box-office data analysis

Wang, Y., Ru, Y., & Chai, J. (2018) · Neural Computing and Applications · doi:10.1007/s00521-018-3731-7 · Cited by 13

Approved for External Publication © Copyright 2010 Hewlett-Packard Development Company

Asur, S., & Huberman, B. A. (2014)

Scientific Journal Impact Factor: 3.449 (ISRA), Impact Factor: 2.114

Patel, P., Patel, R., & Agrawal, E. (2016)

Social Media Mining

Choudhery, D., & Leung, C. K.-S. (2017) · International Database Engineering and Applications Symposium (IDEAS) · doi:10.1145/3105831.3105854 · Cited by 45

The power of twitter on predicting box office revenues

Jeon, J., & McSharry, P. (2012) · Strathprints: The University of Strathclyde institutional repository (University of Strathclyde) · Cited by 2

Predictive Model for Box-office Success of Movies Using Social media

Thite, P., Shah, N., & Marakarkandy, B. (2014)