Big Data and Social Data

2015 ◽  
pp. 16-45
Keyword(s):  
Big Data ◽  
Social Data

scholarly journals Big Data Revisited: A Rejoinder

2015 ◽  
Vol 30 (1) ◽  
pp. 70-74 ◽  
Author(s):  
Jannis Kallinikos ◽  
Ioanna D Constantiou
Keyword(s):  
Big Data ◽  
Final Section ◽  
Current Data ◽  
Data Capture ◽  
Sensor Data ◽  
Data Generation ◽  
Social Data ◽  
Use Of Data ◽  
Key Issues ◽  
Communicative Processes

We elaborate on key issues of our paper New games, new rules: big data and the changing context of strategy as a means of addressing some of the concerns raised by the paper's commentators. We initially deal with the issue of social data and the role it plays in the current data revolution. The massive involvement of lay publics as instrumented by social media breaks with the strong expert cultures that have underlain the production and use of data in modern organizations. It also sets apart the interactive and communicative processes by which social data is produced from sensor data and the technological recording of facts. We further discuss the significance of the very mechanisms by which big data is produced as distinct from the very attributes of big data, often discussed in the literature. In the final section of the paper, we qualify the alleged importance of algorithms and claim that the structures of data capture and the architectures in which data generation is embedded are fundamental to the phenomenon of big data.

scholarly journals ANALYSIS ON COGNITIVE SOCIAL DATA FUSION

2020 ◽  
pp. 27-30
Author(s):  
Anandakumar H ◽  
Tamilselvan T ◽  
Nandni S ◽  
Subashree R ◽  
Vinodhini E
Keyword(s):  
Social Media ◽  
Big Data ◽  
Data Fusion ◽  
Data Processing ◽  
Pattern Mining ◽  
Data Representation ◽  
Map Reduce ◽  
User Interest ◽  
Social Data ◽  
Algorithm Mapping

Big data stands for effective handling of large amount of data, research, mining, intelligence. In social media large amount of data uploaded every.Social media handle large amount of data like photo, video, songs and so many using big data. When it comes for big data, a large amount of data should be effectively handled. Big data face various challenges like clustering of data, visualizing, data representation, data processing, pattern mining, tracking of data and analysing behaviour of users. In this paper the Emoji in messages are decoded and Unicode will be set. Based on the Emoji the user interest can be understood in a better way. Then another part involves the replacement of repeated data by using the map Reduce algorithm. Mapping of data with key values used to reduce the size of storage.

scholarly journals Media Sosial Universitas Muhammadiyah Yogyakarta @UMYogya dalam Perspektif Social Big Data

2021 ◽  
Vol 4 (1) ◽  
pp. 81-97
Author(s):  
Ayu Amalia
Keyword(s):  
Social Media ◽  
Big Data ◽  
Social Media Analytics ◽  
Social Data ◽  
Social Big Data

Social big data merupakan potensi pengelolaan big data dengan pendekatan baru yang spesifik merujuk pada data-data yang dihasilkan dari media sosial. Universitas Muhammadiyah Yogyakarta sebagai institusi pendidikan tinggi yang bereputasi dengan media sosial @UMYogya, merupakan kontributor potensial dalam konteks big data. Penelitian ini merupakan penelitian deskriptif yang bertujuan mengungkap potensi media sosial @UMYogya secara kuantitaif dengan menggunakan alat bantu berupa fitur social media analytics. Media sosial sebagai mid-tier influencer memiliki intensitas engagement dengan viewers media sosialnya pada taraf yang cukup signifikan, dengan menerapkan skema pengelolaan media sosial yang merujuk pada diagram big social data, maka media sosial @UMYogya sebagai representasi dari Universitas Muhammadiyah Yogyakarta dapat meningkatkan impact­-nya dengan lebih melibatkan stakeholders dan mengembangkan media sosialnya dengan merujuk pada potensi social big data itu sendiri.

scholarly journals Small Area Model-Based Estimators Using Big Data Sources

2015 ◽  
Vol 31 (2) ◽  
pp. 263-281 ◽  
Author(s):  
Stefano Marchetti ◽  
Caterina Giusti ◽  
Monica Pratesi ◽  
Nicola Salvati ◽  
Fosca Giannotti ◽  
...  
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Small Area ◽  
Small Area Estimation ◽  
The Body ◽  
Statistical Research ◽  
Social Data ◽  
Area Estimation ◽  
Model Based ◽  
Social Data Mining

Abstract The timely, accurate monitoring of social indicators, such as poverty or inequality, on a finegrained spatial and temporal scale is a crucial tool for understanding social phenomena and policymaking, but poses a great challenge to official statistics. This article argues that an interdisciplinary approach, combining the body of statistical research in small area estimation with the body of research in social data mining based on Big Data, can provide novel means to tackle this problem successfully. Big Data derived from the digital crumbs that humans leave behind in their daily activities are in fact providing ever more accurate proxies of social life. Social data mining from these data, coupled with advanced model-based techniques for fine-grained estimates, have the potential to provide a novel microscope through which to view and understand social complexity. This article suggests three ways to use Big Data together with small area estimation techniques, and shows how Big Data has the potential to mirror aspects of well-being and other socioeconomic phenomena.

Predicting Flu-Rate Using Big Data Analytics Based on Social Data and Weather Conditions

2017 ◽  
Vol 23 (12) ◽  
pp. 12775-12779 ◽  
Author(s):  
Shikha Verma ◽  
Younghee Park ◽  
Mihui Kim
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Weather Conditions ◽  
Social Data
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