Kiran Zahra

Social media platforms such as Twitter provide convenient ways to share and consume important information during disasters and emergencies. Information from bystanders and eyewitnesses can be useful for law enforcement agencies and humanitarian organizations to get firsthand and credible information about an ongoing situation to gain situational awareness among other uses. However, identification of eyewitness reports on Twitter is challenging for many reasons. This work investigates the sources of tweets and classifies them into three types (i) direct eyewitnesses, (ii) indirect eyewitness, and (iii) vulnerable accounts. Moreover, we investigate various characteristics associated with each kind of eyewitness account. We observe that words related to perceptual senses (feeling, seeing, hearing) tend to be present in direct eyewitness messages, whereas emotions, thoughts, and prayers are more common in indirect witnesses. We believe these characteristics can help make more efficient ...

Twitter is a widely known platform for speedy diffusion of views, ideas and information during different events. It has widely been used during disasters to communicate evacuation plans, help calls, and damage assessment. Reliability of information accessed during mass emergencies from social media for decision making is very important. In this research we reveal different aspects of credibility, granularity of geographic information reported in tweets and use of Naïve Bayes for tweet classification from the users of Europe and Asia. We used user-based features to assess credibility. Toponyms from tweet text are extracted with its frequency to reveal geographic feature granularity in the tweets. Naïve Bayes is used to classify tweets which is trained on one geographic location and tested for the event from another geographic region. Our results show that credibility assessment shows a complex picture for Italy and Myanmar based on user-based features. So-called fine geographic granu...

Education is the most fundamental right in the current situation, and it is an essential element of economic growth. No country can achieve economic development and goals without investing in education. Pakistan’s economic development is possible when education is equal for both men and women, but the government did not give importance to the sector as it deserved. This study investigated the determinants of female higher education in Pakistan and the impact of women's education on the economic growth of Pakistan. This study utilized time-series data from 1991 to 2019. The autoregressive distribution lag (ARDL) model is applied to estimate the impact. The result shows that in Pakistan, education expenditure has no positive effect on female education. In contrast, a positive relationship between female higher education and GDP growth exists, but this relation is not strong in the short run and long run.