Implementation of Classification of Geolocation of Country from Worldwide Tweets

Social media are progressively being employed within the scientific community as key supply of knowledge to assist perceive various natural and social phenomena, and this has prompted the event of a good vary of process data processing tools that may extract data from social media for each post-hoc and real time analysis. The rise of interest in mistreatment social media as a supply for analysis has actuated braving the challenge of mechanically geo-locating tweets, given the dearth of specific location data within the majority of tweets. In distinction to abundant previous work that has targeted on location classification of tweets restricted to a selected country, here we tend to undertake the task during a broader context by classifying international tweets at the country level that is up to now undiscovered during a time period situation. We tend to analyze the extent to that a tweet’s country of origin maybe determined by creating use of eight tweet-inherent options for classification

Istraživački potencijal Twittera – izbor iz literature

Prva istraživanja Twittera kao društvene mreže dokazala su njegov globalni karakter i znanstveni potencijal već godinu dana nakon njegove pojave. Navedeni su naslovi 10 članaka kojima su cjeloviti tekstovi slobodno dostupni na internetu, a koji ukazuju na istraživački potencijal Twittera na području geoinformacija i kartografije

A Survey on Classification of Geolocation of Country from Worldwide Tweets

Social media are progressively being utilized as a part of mainstream researchers as a key wellspring of information to help comprehend differing common and social term, and this has prompted the advancement of an extensive variety of computational information mining apparatuses that can remove learning from web-based social networking for both ad-hoc and ongoing examination. The expansion of enthusiasm for utilizing web-based social networking as a hotspot for look into has roused handling the test of consequently geolocating tweets, given the absence of express area data in the lion's share of tweets. As opposed to much past work that has concentrated on area grouping of tweets limited to a particular nation, here we attempt the assignment in a more extensive setting by ordering worldwide tweets at the country level, which is so far unexplored in an ongoing situation. We break down the degree to which a tweet's nation of starting point can be dictated by making utilization of eight tweet-inherent highlights for classification

Dobrovoljno kartografiranje u kriznim situacijama

Fizički senzori diljem svijeta generiraju ogromnu količinu podataka, ali to čine i ljudi. Ljudi s mobilnim telefonima impresivna su masa multimedijskih senzora. Ta sve veća mreža ljudskih senzora nazvana je i novim „živčanim sustavom“ našega planeta. Taj sustav generira značajnu količinu podataka u stvarnom vremenu preko SMS-a i platformi društvenih medija kao što su Twitter, Facebook, YouTube i Flickr – osobito u kriznim situacijama. Dan je sažeti prikaz članka u kojem se izvještava o dobrovoljnom kartografiranju u kriznim situacijama u Keniji, Haitiju, Rusiji, Libiji, Japanu i Siriji

Authenticity of Geo-Location and Place Name in Tweets

The place name and geo-coordinates of tweets are supposed to represent the possible location of the user at the time of posting that tweet. However, our analysis over a large collection of tweets indicates that these fields may not give the correct location of the user at the time of posting that tweet. Our investigation reveals that the tweets posted through third party applications such as Instagram or Swarmapp contain the geo-coordinate of the user specified location, not his current location. Any place name can be entered by a user to be displayed on a tweet. It may not be same as his/her exact location. Our analysis revealed that around 12% of tweets contains place names which are different from their real location. The findings of this research can be used as caution while designing location-based services using social media

Enhancing Disaster Management Through Social Media Analytics To Develop Situation Awareness: What Can Be Learned From Twitter Messages About Hurricane Sandy?

Twitter became an important channel to contribute and consume all kinds of information, especially in times of disasters, when people feel the need for fast, real-time flows of information. Given the wealth of information Twitter provides, that information can be used by practitioners and researchers alike to study what people affected by a disaster talk about, e.g., to develop a situation awareness and to coordinate disaster management accordingly. In our research, we analyze 11 million tweets that deal with hurricane Sandy, one of the strongest hurricanes that ever hit the US east coast in 2012. First, we extract the tweets by narrowing down the hurricane affected path along the US east coast, based on geo-spatial information. Further, drawing on the situation awareness literature and previous coding schemes, we analyze the nature and characteristics of the tweets. Our research reveals that there are significantly more tweets from original sources than from secondary sources and that individuals tend to share valuable personal experiences and observations at the time of disasters. In analyzing those individual level perceptions, we illustrate how one can generate situation awareness at the collective level. This situation awareness will enhance the decision-making of disaster management agencies at the time of uncertain and volatile situations