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

Design and Application of a Multi-Variant Expert System Using Apache Hadoop Framework

Ibrahim, M., & Bajwa, I. (2018) · Sustainability · doi:10.3390/su10114280 · Cited by 12

Understanding Social Media's Take on Climate Change through Large-Scale Analysis of Targeted Opinions and Emotions.

Pathak, N., Henry, M. J., & Volkova, S. (2017) · National Conference on Artificial Intelligence · Cited by 13

Sosyal Medyada Gelişmeleri Kaçırma Korkusunun Kişinin Tatil Satın Alma Niyetine Etkisi

Çetinkaya, F. Ö., & Şahbaz, R. P. (2019) · Turk Turizm Arastirmalari Dergisi · doi:10.26677/tr1010.2019.168 · Cited by 15

Sales Prediction with Social Media Analysis

Ahn, H.-I., & Spangler, W. S. (2014) · Annual SRII Global Conference · doi:10.1109/srii.2014.37 · Cited by 13

Harvesting Social Signals to Inform Peace Processes Implementation and Monitoring

Nigam, A., Dambanemuya, H. K., Joshi, M., & Chawla, N. V. (2017) · Big Data · doi:10.1089/big.2017.0055 · Cited by 13

Influential spreaders in the political Twitter sphere of the 2013 Malaysian general election

Sun, H., Ch’ng, E., & See, S. C. W. (2018) · Industrial Management & Data Systems · doi:10.1108/imds-09-2017-0409 · Cited by 13

Do Cascades RecurPreprint

Cheng, J., Adamic, L. A., Kleinberg, J. M., & Leskovec, J. (2016) · arXiv (Cornell University) · Cited by 13

Quantifying Regional Differences in the Length of Twitter Messages

Alis, C., Lim, M. T., Moat, H. S., Barchiesi, D., Preis, T., & Bishop, S. R. (2015) · PLoS ONE · doi:10.1371/journal.pone.0122278 · Cited by 12

Dynamic logistic regression and variable selection: Forecasting and contextualizing civil unrest

Bakerman, J., Pazdernik, K., Korkmaz, G., & Wilson, A. G. (2021) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2021.07.003 · Cited by 12

Neuvermessung der Datenökonomie

Islam, Z., Örsal, D. D. K., Maass, C. H., Roth, F., Scheffer, N., Schneider, H., Sturm, S., & Vöpel, H. (2021) · Edition HWWI · doi:10.15460/hup.hwwi.6.212 · Cited by 12

Prescriptive graph analytics on the digital transformation in healthcare through user-generated content

Caño-Marín, E., Mora‐Cantallops, M., & Sánchez‐Alonso, S. (2023) · Annals of Operations Research · doi:10.1007/s10479-023-05495-z · Cited by 15

High Quality Microblog Extraction Based on Multiple Features Fusion and Time-Frequency Transformation

Peng, M., Huang, J., Fu, H. Q., Zhu, J., Zhou, L., He, Y., & Li, F. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-41154-0_14 · Cited by 12

Reorder user's tweets

Shen, K., Wu, J., Zhang, Y., Han, Y., Yang, X., Song, L., & Gu, X. (2013) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/2414425.2414431 · Cited by 12

Weaving Twitter stream into Linked Data a proof of concept framework

Sahito, F., Latif, A., & Slany, W. (2011) · International Conference on Emerging Technologies · doi:10.1109/icet.2011.6048497 · Cited by 12

Boosting election prediction accuracy by crowd wisdom on social forums

Wang, M.-H., & Lei, C. (2016) · IEEE Consumer Communications and Networking Conference · doi:10.1109/ccnc.2016.7444805 · Cited by 12

STH-Bass: A Spatial-Temporal Heterogeneous Bass Model to Predict Single-Tweet Popularity

Yan, Y., Tan, Z., Gao, X., Tang, S., & Chen, G. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-32049-6_2 · Cited by 12

Prediction Model of the Stock Market Index Using Twitter Sentiment Analysis

Caliñgo, A. R., Sison, A. M., & Tanguilig, B. T. (2016) · International Journal of Information Technology and Computer Science · doi:10.5815/ijitcs.2016.10.02 · Cited by 12

Sensing Social Media: A Range of Approaches for Sentiment Analysis

Paltoglou, G., & Thelwall, M. A. (2016) · Understanding complex systems · doi:10.1007/978-3-319-43639-5_6 · Cited by 12

Mining trailers data from youtube for predicting gross income of movies

Rahim, M. S., Chowdhury, A. E., Islam, M. A., & Islam, M. R. (2017) · IEEE Region Humanitarian Technology Conference · doi:10.1109/r10-htc.2017.8289020 · Cited by 12

Integrating Time Series with Social Media Data in an Ontology for the Modelling of Extreme Financial Events

Qu, H., Nascimento, M. S., Qomariyah, N. N., & Kazakov, D. (2016) · White Rose Research Online (University of Leeds, The University of Sheffield, University of York) · Cited by 12

Sources and Types of Big Data for Macroeconomic Forecasting

Garboden, P. M. E. (2019) · Advanced studies in theoretical and applied econometrics · doi:10.1007/978-3-030-31150-6_1 · Cited by 12

A Bayesian-Based Approach for Public Sentiment Modeling

Chen, Y., Ji, W., & Wang, Q. (2019) · Winter Simulation Conference · doi:10.1109/wsc40007.2019.9004846 · Cited by 12

Big Data and Happiness

Rossouw, S., & Greyling, T. (2020) · Springer eBooks · doi:10.1007/978-3-319-57365-6_183-1 · Cited by 15

Generating Personas for Products on Social Media: A Mixed Method to Analyze Online Users

Tan, H., Peng, S.-L., Liu, J., Zhu, C.-P., & Zhou, F. (2021) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2021.1990520 · Cited by 12

Mining quad closure patterns in Instagram

Müngen, A. A., & Kaya, M. (2016) · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · doi:10.1109/asonam.2016.7752352 · Cited by 12

280 characters to the White House: predicting 2020 U.S. presidential elections from twitter data

Rizk, R., Rizk, D., Rizk, F., & Hsu, S. (2023) · Computational and Mathematical Organization Theory · doi:10.1007/s10588-023-09376-5 · Cited by 12

Predictions based on Twitter — A critical view on the research process

Madlberger, L., & Almansour, A. (2014) · International Conference on Data and Software Engineering · doi:10.1109/icodse.2014.7062667 · Cited by 12

The adoption of social networking technologies in cinema releases

Westland, J. C. (2012) · Information Technology and Management · doi:10.1007/s10799-012-0114-0 · Cited by 12

Hybrid multi-tenant cache management for virtualized ISP networks

Claeys, M., Tuncer, D., Famaey, J., Charalambides, M., Latré, S., George Pavlou, A., & Turck, F. D. (2016) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2016.04.004 · Cited by 12

The Usage of Social Media Text Data for the Demand Forecasting in the Fashion Industry

Beheshti-Kashi, S., & Thoben, K. (2015) · Lecture notes in logistics · doi:10.1007/978-3-319-23512-7_72 · Cited by 12

Opening big in box office? Trailer content can help

Tadimari, A., Kumar, N., Guha, T., & Narayanan, S. S. (2016) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2016.7472183 · Cited by 12

Audience Ratings Prediction of TV Dramas Based on the Cast and Their Popularity

Fukushima, Y., Yamasaki, T., & Aizawa, K. (2016) · IEEE International Conference on Multimedia Big Data · doi:10.1109/bigmm.2016.24 · Cited by 12

Movie aspects, tweet metrics, and movie revenues: The influence of iOS vs. Android

Zimbra, D. K., Sarangee, K. R., & Jindal, R. P. (2017) · Decision Support Systems · doi:10.1016/j.dss.2017.08.002 · Cited by 12

Private attribute inference from Facebook’s public text metadata: a case study of Korean users

Choi, D., Lee, Y., Kim, S., & Kang, P. (2017) · Industrial Management & Data Systems · doi:10.1108/imds-07-2016-0276 · Cited by 12

Sentiment analysis using Konstanz Information Miner in social networks

Baydogan, C., & Alataş, B. (2018) · International Symposium on Digital Forensics and Security (ISDFS) · doi:10.1109/isdfs.2018.8355395 · Cited by 12

An LSTM Model for Predicting Cross-Platform Bursts of Social Media Activity

Bidoki, N. H., Mantzaris, A. V., & Sukthankar, G. (2019) · Information · doi:10.3390/info10120394 · Cited by 14

Predicting Success of a Movie from Youtube Trailer Comments using Sentiment Analysis

Timani, H., Shah, P., & Joshi, M. (2019) · International Conference on Computing for Sustainable Global Development · Cited by 12

Research on Network Public Opinion Analysis and Monitor Method Based on Big Data Technology

Liu, D., Zhang, H., Yu, H., Zhao, X., Wan, M., Liu, X., & Ma, L. (2020) · IEEE International Conference on Electronics Information and Emergency Communication · doi:10.1109/iceiec49280.2020.9152232 · Cited by 12

Learning to Learn Sales Prediction with Social Media Sentiment

Lin, Z., Madotto, A., Winata, G. I., Liu, Z., Xu, Y., Cong, G., & Fung, P. (2019) · Cited by 11

Identifying Polarity in Tweets from an Imbalanced Dataset about Diseases and Vaccines Using a Meta-Model Based on Machine Learning Techniques

Rodríguez‐González, A., Tuñas, J. M., Santamaría, L. P., Peces-Barba, D. F., Menasalvas, E., Jaramillo, A., Cotarelo, M., Fernández, A. J. C., Arce, A., & de Miguel, Á. G. (2020) · Applied Sciences · doi:10.3390/app10249019 · Cited by 13

Competitive Product Identification and Sales Forecast Based on Consumer Reviews

Zhang, G., & Qiu, H. (2021) · Mathematical Problems in Engineering · doi:10.1155/2021/2370692 · Cited by 12

Detecting and Analyzing Influenza Epidemics with Social Media in China

Zhang, F., Luo, J., Li, C., Wang, X., & Zhao, Z. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-06608-0_8 · Cited by 13

Using Social Media to Predict Future Events with Agent-based Markets

Bothos, E., Apostolou, D., & Mentzas, G. N. (2010) · IEEE Intelligent Systems · doi:10.1109/mis.2010.132 · Cited by 12

Designing Fitness Apps Using Persuasive Technology: A Text Mining Approach

Yoganathan, D., & Sangaralingam, K. (2015) · Journal of the Association for Information Systems · Cited by 12

On Complex Event Processing for Real-Time Situational Awareness

Stojanović, N., & Artikis, A. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-22546-8_10 · Cited by 12

Impact of Online Firm Generated Content (FGC) on Supply Chain Performance: An Empirical Analysis

Swain, A. K., & Cao, Q. (2014) · Hawaii International Conference on System Sciences (HICSS) · doi:10.1109/hicss.2014.77 · Cited by 13

Prediction of popular tweets using Similarity Learning

Ahmed, H., Razzaq, M. A., & Qamar, A. M. (2013) · International Conference on Emerging Technologies · doi:10.1109/icet.2013.6743524 · Cited by 12

How Can Social Media Lead to Co-Production (Co-Delivery) of New Services for the Elderly Population? A Qualitative Study

Daneshvar, H., Anderson, S., Williams, R., & Mozaffar, H. (2018) · JMIR Human Factors · doi:10.2196/humanfactors.7856 · Cited by 11

Topic and Sentiment Analysis on OSNs: a Case Study of Advertising Strategies on TwitterPreprint

Dacres, S., Haddadi, H., & Purver, M. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1312.6635 · Cited by 13

Using Twitter to predict football outcomesPreprint

Kampakis, S., & Adamides, A. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1411.1243 · Cited by 12

An Empirical Study on Social Media Behaviour of Consumers and Social Media Marketing Practices of MarketersPreprint

Vij, S., & Sharma, J. P. (2013) · SSRN Electronic Journal · Cited by 12

Improved Forecasting of Cryptocurrency Price using Social SignalsPreprint

Glenski, M., Weninger, T., & Volkova, S. (2019) · RePEc: Research Papers in Economics · doi:10.48550/arxiv.1907.00558 · Cited by 20

Crawling Twitter data through API: A technical/legal perspectivePreprint

Sohail, S., Khan, M. M., Arsalan, M., Khan, A., Siddiqui, J., Hasan, S. H., & Alam, M. A. (2021) · arXiv.org · doi:10.48550/arxiv.2105.10724 · Cited by 23

The Psychology Behind People's Decision to Forward Disaster-Related TweetsPreprint

Li, H., Sakamoto, Y., Chen, R., & Tanaka, Y. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2473544 · Cited by 12

Crime Rate Detection Based on Text Mining on Social Media Using Logistic Regression Algorithm

Permana, M. A., Thohir, M. I., Mantoro, T., & Ayu, M. A. (2021) · IEEE International Conference on Computing, Engineering and Design (ICCED) · doi:10.1109/icced53389.2021.9664846 · Cited by 11

The paradox of digital marketing: Sustainable framework for effective strategies and regulatory challenges

Serhan, T. F. A. A., & Zhang, S. (2025) · Information Development · doi:10.1177/02666669241303451 · Cited by 11

Uncovering information from social media hyperlinks: An investigation of twitter

Vaughan, L. Q. (2015) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23486 · Cited by 11

Linking Neuroimaging with Functional Linguistic Analysis to Understand Processes of Successful Communication

O’Donnell, M. B., & Falk, E. B. (2015) · Communication Methods and Measures · doi:10.1080/19312458.2014.999751 · Cited by 14

Co-Creating Value in Systems Development: A Shift towards Service-Dominant Logic

Babb, J. S., & Keith, M. J. (2012) · Cited by 11

The Viability of StockTwits and Google Trends to Predict the Stock Market

Loughlin, C. (2013) · Cited by 11

Predicting the Future of Investor Sentiment with Social Media in Stock Exchange Investments: A Basic Framework for the DAX Performance Index

Lugmayr, A. R. (2012) · Springer eBooks · doi:10.1007/978-3-642-28897-5_33 · Cited by 11

Mining and Visualizing Social Data to Inform Marketing Decisions

Treboux, J., Cretton, F., Évéquoz, F., Calvé, A. L., & Genoud, D. (2016) · International Conference on Advanced Information Networking and Applications (AINA) · doi:10.1109/aina.2016.130 · Cited by 11

Crowdsourcing based Timeline Description of Urban Emergency Events using Social Media

Xu, Z. (2016) · International Journal of Ad Hoc and Ubiquitous Computing · doi:10.1504/ijahuc.2017.10001956 · Cited by 11

Domain Specific Lexicon Generation through Sentiment Analysis

Shaukat, K., Hameed, I. A., Luo, S., Javed, I., Iqbal, F., Faisal, A., Masood, R., Usman, A., Shaukat, U., Hassan, R., et al. (2020) · International Journal of Emerging Technologies in Learning (iJET) · doi:10.3991/ijet.v15i09.13109 · Cited by 11

Social media activity forecasting with exogenous and endogenous signals

Ng, K. W., Horawalavithana, S., & Iamnitchi, A. (2022) · Social Network Analysis and Mining · doi:10.1007/s13278-022-00927-3 · Cited by 13

Fake News Detection of South African COVID-19 Related Tweets using Machine Learning

Khan, Y., & Thakur, S. C. (2022) · International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD) · doi:10.1109/icabcd54961.2022.9856272 · Cited by 12

Tweet‐biased summarization

Yulianti, E., Huspi, S. H., & Sanderson, M. (2015) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23496 · Cited by 11

Assessing the Impact of the Fukushima Nuclear Disaster on Policy Dynamics and the Public Sphere

Hassard, H. A., Swee, J. K. Y., Ghanem, M. M., & Unesaki, H. (2013) · Procedia Environmental Sciences · doi:10.1016/j.proenv.2013.02.072 · Cited by 11

THE ACCEPTANCE, USAGE AND IMPACT OF SOCIAL MEDIA AMONG UNIVERSITY STUDENTS

Destiana, I., & Salman, A. (2015) · e-Bangi · Cited by 11

Weak Signals as Predictors of Real-World Phenomena in Social Media

Charitonidis, C., Rashid, A., & Taylor, P. J. (2015) · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · doi:10.1145/2808797.2809332 · Cited by 11

Wisdom of fusion: Prediction of 2016 Taiwan election with heterogeneous big data

Xie, Z., Liu, G., Wu, J., Wang, L., & Liu, C. (2016) · International Conference on Service Systems and Service Management · doi:10.1109/icsssm.2016.7538625 · Cited by 11

Cultural Event Management and Urban e-Planning Through Bottom-Up User Participation

Corallo, A., Trono, A., Fortunato, L., Pettinato, F., & Schina, L. (2017) · International Journal of E-Planning Research · doi:10.4018/ijepr.2018010102 · Cited by 11

Des données du Web pour faire de la sociologie… du Web ?

Beuscart, J.-S. (2017) · Collège de France eBooks · doi:10.4000/books.cdf.5009 · Cited by 10

Modeling information diffusion in time-varying community networks

Cui, X., & Zhao, N. (2017) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/1.5002577 · Cited by 11

Automated Discovery of Product Feature Inferences Within Large-Scale Implicit Social Media Data

Tuarob, S., Lim, S., & Tucker, C. S. (2018) · Journal of Computing and Information Science in Engineering · doi:10.1115/1.4039432 · Cited by 11

Opinion leaders’ prediction for monitoring the product reputation

Ennaji, F. Z., Fazziki, A. E., Abdallaoui, H. E. A. E., Benslimane, D., & Sadgal, M. (2018) · International Journal of Web Information Systems · doi:10.1108/ijwis-03-2018-0016 · Cited by 11

Content-based Classification of Political Inclinations of Twitter Users

Giovanni, M. D., Brambilla, M., Ceri, S., Daniel, F., & Ramponi, G. (2018) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata.2018.8622040 · Cited by 11

Twitter-Informed Crowd Flow Prediction

Goh, G. S. W., Koh, J. Y., & Zhang, Y. (2018) · IEEE ... International Conference on Data Mining workshops · doi:10.1109/icdmw.2018.00097 · Cited by 11

Client-Driven Personalized Trailer Framework Using Thumbnail Containers

Mujtaba, G., & Ryu, E. (2020) · IEEE Access · doi:10.1109/access.2020.2982992 · Cited by 11

The impact of Facebook on real estate sales

Shi, H., Ma, Z., Chong, D., & He, W. (2020) · Journal of Management Analytics · doi:10.1080/23270012.2020.1858985 · Cited by 11

The impact of events on metal futures based on the perspective of Google Trends

Wei, H., Guo, Y., Yu, Z., & Cheng, H. C. (2021) · Resources Policy · doi:10.1016/j.resourpol.2021.102286 · Cited by 11

A Survey of Social Web Mining Applications for Disease Outbreak Detection

Bello-Orgaz, G., Hernandez-Castro, J. C., & Camacho, D. (2014) · Studies in computational intelligence · doi:10.1007/978-3-319-10422-5_36 · Cited by 11

The Impact of Social Media on the Social, Political and Economic Environments in Africa

Adelaja, O. (2013) · Advances in human and social aspects of technology book series · doi:10.4018/978-1-4666-4197-6.ch019 · Cited by 11

The Structure of Citizen Bystander Offering Behaviors Immediately After the Boston Marathon Bombing

LaLone, N. J., Toups, Z. O., & Tapia, A. (2020) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2020.266 · Cited by 11

Sentiment Analysis on Twitter Data: Comparative Study on Different Approaches

Rahman, M. A., Sadat, M., & Siddik, S. (2021) · International Journal of Intelligent Systems and Applications · doi:10.5815/ijisa.2021.04.01 · Cited by 11

Detecting Events and Patterns in Large-Scale User Generated Textual Streams with Statistical Learning MethodsPreprint

Lampos, V. (2012) · arXiv.org · doi:10.48550/arxiv.1208.2873 · Cited by 14

Reliability of Sentiment Mining Tools: A comparison of Semantria and Social Mention

Lawrence, L. P. (2014) · Cited by 11

A Big Data Analysis of the Factors Influencing Movie Box Office in China

WenTao, G., Lam, K. M., Chiu, D. K. W., & Ho, K. K. W. (2021) · Advances in data mining and database management book series · doi:10.4018/978-1-7998-4963-6.ch011 · Cited by 10

The Impact of Z_score on Twitter Sentiment Analysis

Hamdan, H., Bellot, P., & Béchet, F. (2014) · International Workshop on Semantic Evaluation (SemEval) · doi:10.3115/v1/s14-2113 · Cited by 10

Social media as a source of competitive intelligence in a pharmaceutical corporation

Haataja, J.-E. (2011) · Cited by 10

Sequel movie revenue prediction model based on sentiment analysis

Ahmad, I. S., Bakar, A. A., Yaakub, M. R., & Darwich, M. (2020) · Data Technologies and Applications · doi:10.1108/dta-10-2019-0180 · Cited by 10

The effect of TV drama piracy: An analysis of digital piracy users, internet buzz, and TV drama viewership

Kim, D., Park, K., & Bang, Y. (2022) · Information & Management · doi:10.1016/j.im.2022.103599 · Cited by 10

Challenges of Knowledge Management amidst Rapidly Evolving Tools of Social Media

Chugh, R., & Joshı, M. (2019) · IGI Global eBooks · doi:10.4018/978-1-7998-0417-8.ch037 · Cited by 10

Predictive competitive intelligence with prerelease online search traffic

Schaer, O., Kourentzes, N., & Fildes, R. A. (2022) · Production and Operations Management · doi:10.1111/poms.13790 · Cited by 11

How do we spread on Twitter?

Stattner, E., Eugénie, R., & Collard, M. (2015) · International Conference on Research Challenges in Information Science (RCIS) · doi:10.1109/rcis.2015.7128894 · Cited by 10

Semantic Characterization of Tweets Using Topic Models

García-Silva, A., Rodrı́guez-Doncel, V., & Corcho, Ó. (2013) · International Journal on Semantic Web and Information Systems · doi:10.4018/ijswis.2013070101 · Cited by 10

Bestsellers and Blockbusters: Movies, Music, and Books

Walls, W. D. (2013) · Handbook of the economics of art and culture · doi:10.1016/b978-0-444-53776-8.00008-8 · Cited by 10

A Survey on Role of Intelligent Community and Social Networking to Enhance Learning Process of Students and Professionals

S.Patel, A., Darji, H., & Mujapara, J. A. (2013) · International Journal of Computer Applications · doi:10.5120/11829-7530 · Cited by 10

Unlocking Super Bowl Insights

Dai, X., & Prout, R. (2016) · Multidisciplinary International Social Networks Conference (MISNC) · doi:10.1145/2955129.2955148 · Cited by 10

Role of Online Data from Search Engine and Social Media in Healthcare Informatics

Nawaz, M. S., Mustafa, R. U., & Lali, M. I. U. (2017) · Advances in bioinformatics and biomedical engineering book series · doi:10.4018/978-1-5225-2607-0.ch011 · Cited by 10

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)