TWITTER ANALYTICS FOR INTEGRATED RESEARCH IN BIODIVERSITY ASIAN CONFERENCE ON REMOTE SENSING ACRS 2019

摘要

With the exponential rate of growth in usage of social media, the amount of information generated by the social media users is substantially growing which requires more human resources to analyse everything, thus not to miss the valuable information. Nowadays, every Facebook post, every Tweet, every blog entry, every social media platform is generating a new bit of information that may produce situational assessment or awareness in various domains. While this can and is being done, the research carried out in response to this is the development of web based geo-visual interface to forage and filter the place, time and theme from Twitter, and thus provides overview and detail on geographical, temporal and thematic tweets for further analytics. The primary streams of this research are - (ⅰ) extraction of geographic information from geotagged tweets and geocoding of that extracted information, (ⅱ) web-based geo-visualization for text artifacts foraging and sense making, and (ⅲ) sentiment analysis by generating the sentiment time series that elicits strong positive, negative ad neutral sentiments from users. By considering the importance of Twitter as one of the premiere social media platforms, the application is executed on several themes and results are having important implications for social intelligence and analytics. This web based place-time-theme indexing application uses biodiversity domain as a part of Indian Bioresource Information Network (IBIN) project of India. The IBIN project is aimed to create and maintain a digitized collection of the biological resources of India garnished from the published information sources and serve it through a common web platform to a diverse range of end users. The diverse amount of biodiversity data is available on social media platform has exploded in the last decade, but making these data available in real-time for generating the useful insights and patterns requires a considerable investment of time and work, both vital considerations for organizations and institutions looking to validate the impact factors of these online works. Therefore, this research model may embrace passion and proactiveness for conservation and protection of bio-resources. This work interrogated the social media content as a relevant source of information and integrated various twitter contents with filtering and foraging mechanisms, derivation of data facets such as sentiments, and visual methods on map for schematizing analyses. This idea to harness and drive new insights and stories from social media messages will reduce the possibility of noisy data and focus only on the information relevant to the particular theme which may leads to different types of analytical insights.