scholarly journals Securing Social Media Data Using Rjb31 Method

2021 ◽  
pp. 222-227
Keyword(s):  
Social Media ◽  
Prime Number ◽  
Secret Key ◽  
Present Stage ◽  
Social Media Data ◽  
Public Data ◽  
Present World ◽  
Media Data

The present world is data world; without this data cannot survive in present stage. This data produced more from social media; This media data is public data; This public data did not have well security; so we applying the Salsa method. This method easily hack the data from the hackers. RBJ31 method has 4 steps. 1. Applying the secret key and multiply that key; 2. To apply the prime number and calculate the S 2and T 2 ; 3. To calculate the EA1 and EA2; 4. To swap the EA1 and EA2 in matrix EnA. The proposed method gives well security while comparing with Salsa method

scholarly journals DATA SECURITY USING RJB32 METHOD

2021 ◽  
Keyword(s):  
Social Media ◽  
Prime Number ◽  
Data Security ◽  
Present Stage ◽  
Public Data ◽  
Present World ◽  
Media Data

The present world is data world; without this data cannot survive in present stage. This data produced more from social media; this media data is public data; This public data not have good security; so to overcome this issue we apply the Salsa method. This method easily hack the data from the hackers. RBJ32 method has 5 steps. 1. Applying the key and multiply that key; 2. To apply the prime number in the S 2 and T 2 ; 3. To calculate the EA1 and EA2; 4. To swap the EA1 and EA2 in matrix EnA; 5. Apply the column operations. The proposed method provides good security while comparing with Salsa method.

scholarly journals Attitudes towards Brands and Advertisements: Qualitative and Thematic Analysis of Social Media Data

2019 ◽  
Author(s):  
Emmanuel Mogaji ◽  
Temitope Farinloye
Keyword(s):  
Social Media ◽  
Research Method ◽  
User Generated Content ◽  
Social Media Data ◽  
Perceptions And Attitudes ◽  
Public Data ◽  
Social Media Platforms ◽  
The Mind ◽  
Media Data ◽  
Insight Into

<div>Social media has been described as a platform for discussing ideas, communicating experiences and exchanging knowledge. It has changed the way individuals interact, providing massive amount of data and rich market insight as customers and brands engage and build relationships. This public declaration is of great concern for any organisation as it transfers the power to shape brand images from the hands of advertisers to the words of consumers’ online connections.</div><div>This chapter sets an agenda proposing the possibilities of qualitatively analysing user-generated content on social media platforms to provide insight into attitudes towards advertisements and their brands. Unlike participants being interviewed in a focus group, filling in questionnaires or neuroscience providing insight into how the mind perceives advertisements which typically requires expensive, bulky equipment and lab-type settings that limit and influence the experience, this is readily available public data which can be thematically analysed to add to existing knowledge.</div><div>Presenting the idea, publicly declared responses to the advertisements of UK banks on Facebook were analysed in order to gain insight into their perceptions and attitudes towards the advertisements and their brands. An outline of how to perform an analysis of user-generated content was provided to buttress the research method. Challenges and limitations of this research method were also considered.</div>

scholarly journals Attitudes towards Brands and Advertisements: Qualitative and Thematic Analysis of Social Media Data

2019 ◽  
Author(s):  
Emmanuel Mogaji ◽  
Temitope Farinloye
Keyword(s):  
Social Media ◽  
Research Method ◽  
User Generated Content ◽  
Social Media Data ◽  
Perceptions And Attitudes ◽  
Public Data ◽  
Social Media Platforms ◽  
The Mind ◽  
Media Data ◽  
Insight Into

<div>Social media has been described as a platform for discussing ideas, communicating experiences and exchanging knowledge. It has changed the way individuals interact, providing massive amount of data and rich market insight as customers and brands engage and build relationships. This public declaration is of great concern for any organisation as it transfers the power to shape brand images from the hands of advertisers to the words of consumers’ online connections.</div><div>This chapter sets an agenda proposing the possibilities of qualitatively analysing user-generated content on social media platforms to provide insight into attitudes towards advertisements and their brands. Unlike participants being interviewed in a focus group, filling in questionnaires or neuroscience providing insight into how the mind perceives advertisements which typically requires expensive, bulky equipment and lab-type settings that limit and influence the experience, this is readily available public data which can be thematically analysed to add to existing knowledge.</div><div>Presenting the idea, publicly declared responses to the advertisements of UK banks on Facebook were analysed in order to gain insight into their perceptions and attitudes towards the advertisements and their brands. An outline of how to perform an analysis of user-generated content was provided to buttress the research method. Challenges and limitations of this research method were also considered.</div>

scholarly journals Big Data in a Crisis? Creating Social Media Datasets for Crisis Management Research

i-com ◽  
2016 ◽  
Vol 15 (3) ◽  
Author(s):  
Christian Reuter ◽  
Thomas Ludwig ◽  
Christoph Kotthaus ◽  
Marc-André Kaufhold ◽  
Elmar von Radziewski ◽  
...  
Keyword(s):  
Social Media ◽  
Crisis Management ◽  
Emergency Services ◽  
Data Sets ◽  
Management Research ◽  
Social Media Data ◽  
Public Data ◽  
Ease Of Access ◽  
Use Of Social Media ◽  
Media Data

AbstractA growing body of research in the area of information systems for crisis management is based on data from social media. After almost every larger disaster studies emerge with the focus on the specific use of social media. Much of this research is based on Twitter data, due to the ease of access of this (mainly public) data, compared to (more closed) data, such as Facebook or Google+. Based on the experience gained from a research project on social media in emergencies and our task to collect social media data sets for other partners, we present the design and evaluation of a graphical user interface that supports those stakeholders (such as emergency services or researchers) that are interested in creating social media datasets for further crisis management research. We do not specifically focus on the analysis of social media data. Rather we aim to support the gathering process and how actors without sophisticated technical skills can be supported to get what they want and especially need: relevant social media data. Within this article, we present a practice-oriented approach and implications for designing tools that support the collection of social media data as well as future work.

Smart De-Identification of Social Media Data

2014 ◽  
Author(s):  
Kathleen M. Carley ◽  
L. R. Carley ◽  
Jonathan Storrick
Keyword(s):  
Social Media ◽  
Social Media Data ◽  
Media Data

Mining Social Media Data to Study the Consequences of Dementia Diagnosis on Caregivers and Relatives (Preprint)

2018 ◽  
Author(s):  
Anika Oellrich ◽  
George Gkotsis ◽  
Richard James Butler Dobson ◽  
Tim JP Hubbard ◽  
Rina Dutta
Keyword(s):  
Social Media ◽  
Family Relationships ◽  
Text Processing ◽  
Automated Analysis ◽  
Health Concern ◽  
Dementia Diagnosis ◽  
Data Set ◽  
Social Media Data ◽  
Real Time Processing ◽  
Media Data

BACKGROUND Dementia is a growing public health concern with approximately 50 million people affected worldwide in 2017 and this number is expected to reach more than 131 million by 2050. The toll on caregivers and relatives cannot be underestimated as dementia changes family relationships, leaves people socially isolated, and affects the finances of all those involved. OBJECTIVE The aim of this study was to explore using automated analysis (i) the age and gender of people who post to the social media forum Reddit about dementia diagnoses, (ii) the affected person and their diagnosis, (iii) relevant subreddits authors are posting to, (iv) the types of messages posted and (v) the content of these posts. METHODS We analysed Reddit posts concerning dementia diagnoses. We used a previously developed text analysis pipeline to determine attributes of the posts as well as their authors to characterise online communications about dementia diagnoses. The posts were also examined by manual curation for the diagnosis provided and the person affected. Furthermore, we investigated the communities these people engage in and assessed the contents of the posts with an automated topic gathering technique. RESULTS Our results indicate that the majority of posters in our data set are women, and it is mostly close relatives such as parents and grandparents that are mentioned. Both the communities frequented and topics gathered reflect not only the sufferer's diagnosis but also potential outcomes, e.g. hardships experienced by the caregiver. The trends observed from this dataset are consistent with findings based on qualitative review, validating the robustness of social media automated text processing. CONCLUSIONS This work demonstrates the value of social media data sources as a resource for in-depth studies of those affected by a dementia diagnosis and the potential to develop novel support systems based on their real time processing in line with the increasing digitalisation of medical care.

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