Identifying Leadership Characteristics from Social Media Data during Natural Hazards using Personality Traits

Abstract

With the availability of smart devices and affordable data plans, social media platforms have become the primary source of information dissemination across geographically dispersed users/locations. it has shown great potential across different application domains including event detection, opinion analysis, recommendation, and prediction. However, the process of extracting useful information from the collected voluminous social media data during natural hazards is a standing problem that needs significant attention from the research community. The fine-grained knowledge detailing users' participation in information spreading could be advantageous in developing a reliable social network for the adverse events (Natural Hazards, Man-made attacks etc.). However, there has been no such findings related to identification of leader and their leadership characteristics associated with natural hazards in previous studies. We have collected 20.6 million tweets which were posted by 5.3 million users, during distinct devastating hazards namely-Floods, Hurricane, Earthquake and Typhoons. To achieve the goal, we divided our work in to three parts. Firstly, classify the collected crises data into four domains i.e resource, causality, news, and sympathy by employing deeper recurrent neural network model. Secondly, we used statistical physics of complex network to recognize local as well as global prominent leaders. At last, we curate leadership characteristics in terms of their big five personality traits and emotional traits. Our experimental, results find evidence that local leadership behaviour characteristics are significantly different from global potentials. Where as we also finds that some behaviour traits were certain to classified domains (resource, causality, news, and sympathy) and some were certain to hazard divisions, though emotional characteristics remained consistent. Later, we conclude that local potentials leaders have comparatively higher emotional strength. Furthermore, when the complete local network structure is unavailable, we find that the dynamic rank is reliable indexing proxy for local potentials. The current study, provide useful insight to understand how leadership characteristics are influenced to hazards, domains and centrality of users. Nowadays, billions of active users over worldwide use social network platforms (SNPs) to interact with each other and shares their day to day activity over platforms like Twitter, Facebook, Tumbler and many more. SNPs have an ample amount of real-time information sources pertinent to real-world events, predominately during any natural hazards or mass crises. These platforms play a vital role to disseminate any information among users through online social interaction 1-3. The previous study on information dissemination reveals that few influential knowledge spreaders (IKs) have the characteristics that can shape millions of users viewpoint 4. Therefore identification of IKs holds immense practical importance and also in recent years it attracted the considerable at...

Personality of Public Health Organizations’ Instagram Accounts and According Differences in Photos at Content and Pixel Levels

“…In addition, the personality traits, except for neuroticism, of public health organizations’ Instagram accounts were predicted from the photo features with an acceptable level of accuracy. Given that the personality of individual users was shown to be predictable from their photo features [ 15 , 34 ], this result can be meaningful in that organizational accounts in social media can be investigated from the perspective of personality which has been employed for examining individual users’ accounts.…”

“…Their results indicated that extraversion, emotional stability, and agreeableness were positively associated with cost efficiency and profitability, while conscientiousness were negatively associated with them. Agarwal and Toshniwal [ 34 ] analyzed tweets under various natural hazards conditions and found that Twitter users with a higher level of extraversion and agreeableness uploaded more tweets of leadership concerning behaviors under crisis situations.…”

Improving the accuracy of text classification using stemming method, a case of non-formal Indonesian conversation

“…The results of the study are in the form of useful insights that the characteristics of the leadership are influenced by hazard, domain, and user centrality. The results are important for assessing the quality of prospective leaders based on their characteristics [22].…”

The influence of sustainable branding and opinion leaders on international students’ intention to study: a case of Universiti Sains Malaysia

“…In other words, they refer to individuals whose opinions influence others’ decision to choose or abandon a particular thing. The source of information reaches these leaders, who then deliver it through messages (Agarwal and Toshniwal, 2020) to their social groups (Kaufmann et al , 2012) such as international students who mostly seek university information through online and social media platforms (Beech, 2015; Bukhari et al , 2020). Furthermore, individuals with strong personalities are more associated socially and likely to impact the opinions of others in a small group circle (Broeder and van Hout, 2019), including students, family and friends (Morrish and Lee, 2011).…”