Introducing COSMOS 2.0
Social media platforms have become an essential outlet to express individuals’ opinions, experience and promote ideas in society. According to estimates, approximately 45 million people in the UK are social media users or 66% of the total population. Daily social media usage is 1 hour 42 minutes in the UK (‘UK Social media statistic for 2020’, 2020). This results in large amounts of communications data and metadata being generated and processed by social media platforms. For instance, 350.000 tweets are posted per minute globally (‘The Number of tweets per day in 2020’, 2020).
Naturally, social media platforms are very interesting data sources for social scientists who are trying to understand and explain the ways in which society works.
One of the biggest challenges social scientists face these days is the ability to access and analyze big data generated by social media platforms. While some platforms make their data publicly available, they require computational skills to access this valuable resource. COSMOS is developed and supported by the Social Data Science Lab to address this very issue.
COSMOS aims to democratise access to big data among academic, private and public sectors, providing ethical access to social media data for researchers.
What is COSMOS?
COSMOS (Collaborative Online Social Media Observatory Software) is a social media analysis tool that can be accessed free of charge by academic and non-profit organisations. COSMOS is an ESRC investment that is funded as part of the Big Data Network.
COSMOS’ main objective is to help researchers who lack technical and computational skills to collect, store, analyse, and visualise huge social media datasets for their research. COSMOS is an all-in-one solution to support these activities. The aim of COSMOS is to lower the barrier to entry into social media data analytics for social scientists and others.
The first release of COSMOS software dates back to 2015. At the Social Data Science Lab, we are very excited to release a revamped version – COSMOS 2.0.
COSMOS can be used for collecting both real-time Twitter data or importing previously collected datasets. It can collect real-time data via the Twitter filter stream API. In most cases, researchers need to analyse social media data within specific parameters such as gender, language, sentiment, keyword or geographical place. They do this to understand the changes in these parameters (and correlation with the public mood, tension, cohesion, etc.) around a particular topic or trigger event.
COSMOS provides filtering and querying features with its new user-friendly interface to meet this need. Its filtering feature can be used for collecting real-time Twitter data while the querying feature can be useful for creating subsets of interests from the data. For example, a COSMOS user can collect data with the keyword ‘pandemic’ and extract the tweets containing the ‘vaccine’ keyword and positive sentiments within the specific time frame selected.
COSMOS provides data analysis at both individual tweet and corpus level. Currently, the types of analyses COSMOS supports are gender and language detection, sentiment analysis, qualitative overview, geospatial location analysis, keyword analysis, longitudinal tweets frequency analysis, social network analysis (Pete Burnap, Javier Conejero, 2014). Here are some details for these analysis types:
Given the above, COSMOS is a very compact and useful software to collect and analyse social media data. It allows users to collect and analyse large-scale social media datasets with its simple and accessible user interface without writing a single line of code!
To install COSMOS, please visit http://socialdatalab.net/COSMOS website and request a download link.
To learn more about how to use COSMOS, please check out the instruction videos on the http://socialdatalab.net/instruction-videos website. In the coming months, we will organise online demo sessions and workshops to demonstrate the capabilities of COSMOS. These sessions will be advertised on our website and social media channels so make sure to keep an eye on our website and follow our Twitter @socdatalab if you are interested in attending these sessions.
If you have any questions, please feel free to contact us at firstname.lastname@example.org.
Pete Burnap, Javier Conejero (2014) ‘COSMOS: Towards an integrated and scalable service for analysing social media on demand’.
‘The Number of tweets per day in 2020’ (2020). Available at: https://www.dsayce.com/social-media/tweets-day/.
‘UK Social media statistic for 2020’ (2020) UK Social media statistic for 2020. Available at: https://www.avocadosocial.com/uk-social-media-statistics-for-2020/.
SentiStrenght (2017). Softpedia. Available at: http://sentistrength.wlv.ac.uk/.
Social Data Science Lab