scholarly journals Identifying Different Types of Social Ties in Events from Publicly Available Social Media Data

2019 ◽  
Author(s):  
Jayesh Gupta ◽  
Hannu Kärkkäinen ◽  
Karan Menon ◽  
Jukka Huhtamäki ◽  
Raghava Mukkamala ◽  
...  
Keyword(s):  
Social Media ◽  
Social Ties ◽  
Social Media Data ◽  
Different Types ◽  
Media Data

scholarly journals Perceiving Residents’ Festival Activities Based on Social Media Data: A Case Study in Beijing, China

2021 ◽  
Vol 10 (7) ◽  
pp. 474
Author(s):  
Bingqing Wang ◽  
Bin Meng ◽  
Juan Wang ◽  
Siyu Chen ◽  
Jian Liu
Keyword(s):  
Social Media ◽  
Language Processing ◽  
Topic Model ◽  
Central Area ◽  
Classification Model ◽  
Social Media Data ◽  
Ring Road ◽  
Different Types ◽  
Spatial Differences ◽  
Media Data

Social media data contains real-time expressed information, including text and geographical location. As a new data source for crowd behavior research in the era of big data, it can reflect some aspects of the behavior of residents. In this study, a text classification model based on the BERT and Transformers framework was constructed, which was used to classify and extract more than 210,000 residents’ festival activities based on the 1.13 million Sina Weibo (Chinese “Twitter”) data collected from Beijing in 2019 data. On this basis, word frequency statistics, part-of-speech analysis, topic model, sentiment analysis and other methods were used to perceive different types of festival activities and quantitatively analyze the spatial differences of different types of festivals. The results show that traditional culture significantly influences residents’ festivals, reflecting residents’ motivation to participate in festivals and how residents participate in festivals and express their emotions. There are apparent spatial differences among residents in participating in festival activities. The main festival activities are distributed in the central area within the Fifth Ring Road in Beijing. In contrast, expressing feelings during the festival is mainly distributed outside the Fifth Ring Road in Beijing. The research integrates natural language processing technology, topic model analysis, spatial statistical analysis, and other technologies. It can also broaden the application field of social media data, especially text data, which provides a new research paradigm for studying residents’ festival activities and adds residents’ perception of the festival. The research results provide a basis for the design and management of the Chinese festival system.

scholarly journals Sentimental analysis on social media data using R programming

2018 ◽  
Vol 7 (2.31) ◽  
pp. 80 ◽  
Author(s):  
Mandava Geetha Bhargava ◽  
Duvvada Rajeswara Rao
Keyword(s):  
Social Media ◽  
Research Field ◽  
Virtual Currency ◽  
Ongoing Research ◽  
Social Media Data ◽  
Digital Currency ◽  
Alternative Currency ◽  
Different Types ◽  
R Programming ◽  
Media Data

Sentimental Analysis is an ongoing research field in Text Mining Arena to determine the situation of market on particular entity such as Product, Services...Etc. and it can be called as computational treatment of reviews, subjectivity and sentiment of text. Cryptocurrency can be explained as a type of digital estate and devised to mechanize as a form of trade and exchanges that uses cryptography as an encryption technique to secure the transactions and acts as decentralized controlled transaction which is opposed to centralized transactions. Cryptocurrency are a type of virtual currency, digital currency and alternative currency, On basis of categorical, there are different architecture and security protocols which are used in the cryptocurrencies to secure transactions, the different types of cryptocurrency are available in the market such as Bitcoin, Litecoin, and Namecoin…etc. This paper focuses on survey on different types of sentimental analysis methods and main contribution of this paper include sentimental analysis of  social media data on different types of cryptocurrencies on basis of categorical and different terms of cryptocurrency such as Cryptocurrency, virtual currency, digital currency and discussed on trends of crypto currency in present market.  

scholarly journals Social Media Data Misuse

2021 ◽  
Author(s):  
Tariq Soussan ◽  
Marcello Trovati
Keyword(s):  
Social Media ◽  
Social Networking Sites ◽  
Modern Method ◽  
High Tech ◽  
Social Media Data ◽  
Ethical Concerns ◽  
Different Types ◽  
Social Media Platforms ◽  
Innovative Enterprise ◽  
Media Data

The present high-tech landscape has allowed institutes to undergo digital transformation in addition to the storing of exceptional bulks of information from several resources, such as mobile phones, debit cards, GPS, transactions, online logs, and e-records. With the growth of technology, big data has grown to be a huge resource for several corporations that helped in encouraging enhanced strategies and innovative enterprise prospects. This advancement has also offered the expansion of linkable data resources. One of the famous data sources is social media platforms. Ideas and different types of content are being posted by thousands of people via social networking sites. These sites have provided a modern method for operating companies efficiently. However, some studies showed that social media platforms can be a source for misinformation at which some users tend to misuse social media data. In this work, the ethical concerns and conduct in online communities has been reviewed in order to see how social media data from different platforms has been misused, and to highlight some of the ways to avoid the misuse of social media data.

Social Media Data Misuse

2021 ◽  
Author(s):  
Tariq Soussan ◽  
Marcello Trovati
Keyword(s):  
Social Media ◽  
Social Networking Sites ◽  
Modern Method ◽  
High Tech ◽  
Social Media Data ◽  
Ethical Concerns ◽  
Different Types ◽  
Social Media Platforms ◽  
Innovative Enterprise ◽  
Media Data

The present high-tech landscape has allowed institutes to undergo digital transformation in addition to the storing of exceptional bulks of information from several resources, such as mobile phones, debit cards, GPS, transactions, online logs, and e-records. With the growth of technology, big data has grown to be a huge resource for several corporations that helped in encouraging enhanced strategies and innovative enterprise prospects. This advancement has also offered the expansion of linkable data resources. One of the famous data sources is social media platforms. Ideas and different types of content are being posted by thousands of people via social networking sites. These sites have provided a modern method for operating companies efficiently. However, some studies showed that social media platforms can be a source for misinformation at which some users tend to misuse social media data. In this work, the ethical concerns and conduct in online communities has been reviewed in order to see how social media data from different platforms has been misused, and to highlight some of the ways to avoid the misuse of social media data.

scholarly journals Emergent social cohesion for coping with community disruptions in disasters

2020 ◽  
Vol 17 (164) ◽  
pp. 20190778 ◽  
Author(s):  
Chao Fan ◽  
Yucheng Jiang ◽  
Ali Mostafavi
Keyword(s):  
Social Media ◽  
Social Cohesion ◽  
Social Ties ◽  
Well Being ◽  
Social Media Data ◽  
Emergency Managers ◽  
Communication History ◽  
And Performance ◽  
Underlying Mechanisms ◽  
Media Data

Social cohesion is an important determinant of community well-being, especially in times of distress such as disasters. This study investigates the phenomena of emergent social cohesion, which is characterized by abrupt, temporary and extensive social ties with the goal of sharing and receiving information regarding a particular event influencing a community. In the context of disasters, emergent social cohesion, enabled by social media usage, could play a significant role in improving the ability of communities to cope with disruptions in recent disasters. In this study, we employed a network reticulation framework to examine the underlying mechanisms influencing emergent social cohesion on social media while communities cope with disaster-induced disruptions. We analysed neighbourhood-tagged social media data (social media data whose users are tagged by neighbourhoods) in Houston, TX, USA, during Hurricane Harvey to characterize four modalities of network reticulation (i.e. enactment, activation, reticulation and performance) giving rise to emergent social cohesion. Our results show that, unlike regular social cohesion, communication history and physical proximity do not significantly affect emergent social cohesion. The results also indicate that weak social ties play an important role in bridging different social network communities, and hence reinforce emergent social cohesion. The findings can inform public officials, emergency managers and decision-makers regarding the important role of neighbourhood-tagged social media, as a new form of community infrastructure, for improving the ability of communities to cope with disaster disruptions through enhanced emergent social cohesion.

Post, Mine, and Be Disturbed: Social Media Data Mining

PsycCRITIQUES ◽  
2016 ◽  
Vol 61 (51) ◽  
Author(s):  
Daniel Keyes
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Social Media Data ◽  
Media Data

Psychological Stress Detection from Social Media Data using a Novel Hybrid Model

2018 ◽  
Vol 6 (8) ◽  
pp. 853-862
Author(s):  
Shaikha Hajera ◽  
Mohammed Mahmood Ali
Keyword(s):  
Social Media ◽  
Psychological Stress ◽  
Hybrid Model ◽  
Stress Detection ◽  
Social Media Data ◽  
Media Data

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

The Psychology of Job Loss: Using Social Media Data to Characterize and Predict Unemployment

2016 ◽  
Author(s):  
Davide Proserpio ◽  
Scott Counts ◽  
Apurv Jain
Keyword(s):  
Social Media ◽  
Job Loss ◽  
Social Media Data ◽  
Media Data
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