Network Diffusion in Information Diffusion over online social networks and example of diffusion in real-life

Through online social networks provide us a platform to share opinions publicly, this mechanism will also lead to the generation of rumors especially in case of emergency. So it is urgent for researchers to figure out the information diffusion dynamics through this new kind of media to prevent rumors.

Information diffusion mechanisms have been widely studied since the advent of complex network theory and infectious disease model. Most models and simulations are based on classical network structures. In information diffusion mechanism by using an online social network dataset from Facebook as an example.

Investigating information diffusion mechanism of online social networks will facilitate governments to guide the direction of public opinion and make proper immunization strategies for rumors in case of emergency.

https://ieeexplore.ieee.org/abstract/document/5563505.

Diffusion is when objects move from high concentration to low concentration. We all can see how the diffusion works, there are an example in real life for difussion. For example food coloring difuse inside the water rapidly, smells of coffee has diffuse through out to the coffee shop like in Starbucks, and watering plants inside has diffusion through soil of the plants.

Fauzi Ahmad
1401164633
MB-41-INT-2

Eculture & Social Networks

Making Content Mining in Twitter with Donald Trump And Hillary Clinton network by using Gephi

These are both of the data tweet that i want to do cleaning data due to the look of list of data more compact and easy to see.

After cleaning the list of data, we have done and this is the data that already cleaned by me. It shows the data of Donald Trump. As we can see in the list of data the name is @realDonaldTrump.
the list of data in here, shows the Hillary Clinton data tweet or @HillaryClinton.
The network runned by ForceAtlas 2 Layout. This network has context with 1855 nodes and 1858 edges in Directed Graph.
This network has context with 468 nodes and it has no nodes in Directed Graph.
Edges network in Modularity Class partition. This network has context with 1855 nodes and 1858 edges in Directed Graph.
Edges network in In-Degree partition. This network has context with 1855 nodes and 1858 edges in Directed Graph.
The result of nodes network

Personal Network of Fauzi Ahmad using R-Studio – igraph

indegree 2 communities freeman degree outdegree

 

so here based on the network graph the key player is Fauzi here, because we can see from the closeness that the name of Fauzi has the biggest score. 

here are the screenshots of my codings at R-Studio:

Review of Connected: The Power Of Six Degrees

Video ini menceritakan sekitar 6 milyar manusia di seluruh dunia pasti terkoneksi dengan manusia lain di seluruh penjuru dunia. Seseorang percaya bahwa koneksi dapat merubah kehidupan. Di dalam video ini pada awalnya, untuk membuktikan teori six degrees kami melakukan survei kecil kepada 40 orang dan menanyakan mengenai six degrees, tetapi beberapa orang yang menjawab mengatakan tidak percaya terhadap teori ini. Namun karena perkembangan zaman dimana teknologi semakin harinya semakin maju dan menemukan berbagai inovasi baru, tidak menutup kemungkinan teori ini pun akan terwujud. Dengan adanya media sosial yang dimana setiap aplikasinya menggabungkan individu di berbagai daerah, bahkan dunia yang akan semakin memudahkan setiap individu melakukan komunikasi atau menjalin koneksi dengan individu lainnya.

Sebelumnya teori ini pun sempat dilakukan oleh seorang actor terkenal yaitu Kevin Bacon, dimana dia melakukan permainan untuk membuktikan siapa saja yang terhubung dengannya di dunia hiburan Hollywood. Setelah permainan ini terkenal, Kevin Bacon pun mendirikan lembaga yang bernama Sixdegrees.org. Semua orang bisa mengikuti permainan ini untuk membuktikan teori Six Degrees of Separation melalui situs www.thekevinbacongame.com dan www.sixdegrees.org

Dengan semakin mudahnya kita terhubung dengan individu lain, kita harus memanfaatkan hal ini dengan sebaik mungkin dengan melakukan hal-hal yang positif didalamnya, agar koneksi kita pun semakin luas dan semakin mudah terhubung dengan individu lain di seluruh penjuru dunia. 

Fauzi Ahmad (1401164633) – MB-40-INT-2

The Computational Social Science And The “New” Network Science

The computational social science could be a method that suitable for us to analyze data deeply. The capacity to collect and analyze massive amounts of data has transformed such fields as biology and physics. The data could be like data sets of millions of people, including location, financial transactions and communications. Communications means how people interact surely offer quantitatively of new perspectives on collective human behavior.

Currently, existing data sets are scattered among many groups, with uneven skills. it is good for us to know easily the data sets for research for example. The computational social science is including to sustainability science because i think the knowledge will stands long on our life.

The “New” Network Science

It proposed a model of generalized affiliation networks in which distance between groups is defined according to some number of social dimensions(e.g.,geography and occupation) , and individuals are characterized by the coordinates of the groups to which they belong. Ties between individuals are then allowed to form with a probability that depends on the distance between the corresponding groups and a tunable homophily (Lazarsfeld & Merton 1954) parameter that biases interactions toward or away from similar nodes. Scale-Free Networks consist of degree distribution which is typically right-skewed with the majority of nodes have less than average degree and a small fraction hubs are many times better connected than average. a practical problem as a combination of the empirical between small-world and scale-free networks that the increasing extent of online activity (as a means of communicating, conducting business, recording activities, etc.) may help at least partially overcome. This is could be effective activities. Network Motifs is like the network that symbolize communities of knowledge for example the World Wide Web. Community Structure is an intermediate scale of analysis between local for example clustering, network motifs and global like connectivity, path lengths structure. Based on the empirical data, local, global, or community are an important but typically overlooked distinction is that between what might be called “symbolic” networks, which can be thought of as network representations of abstract relations between discrete entities, and “interactive” networks, whose links describe tangible interactions that are capable of transmitting information, influence, or material. the relationship between network structure and dynamical consequences is anything but straight forward. For example, itisal most certainly the case that the detail so network structure (as in statistical measures like triad densities or degree distributions) that are relevant to individual and collective behavior will depend on the nature of the particular dynamical process under investigation. Ultrarobust networks that the networks simultaneously minimize the likelihood of individual node failure (due to endogenously generated congestion), and also the impact on global connectivity that results from failures arising out of either endogenous or exogenous causes. The key to ultrarobustness, they find, is that organizational networks must exhibit nonhierarchical ties that extend across all scales.

Fauzi Ahmad (1401164633) – MB-40-INT-2

Digital life: today & tomorrow

In my opinion, in this video shows the amount of device usage culture in this last decade (in 2010) for instance, the interest to using any devices; smartphones, laptops, and tablets at the past. In this video, mostly people tend to use smartphones as their device to communicate and connect to another people in another countries and cities they living by using social media like Facebook and Twitter. Facebook more desirable for most people, in order to able to connect people each other. In that era, the technologies and the internet going sophisticated and faster so that the devices have huge evolution. Start from heavy computer, it means cannot carry to anywhere or only can be installed at one place become lighter, easy to carry, more compact, and minimalist for the size of laptops with a bunch of ability to collect and save very huge data nowadays. In this one decade, the technologies are having a huge growth to dominate the world with sophisticated, easiness, and convenience.

We as a human in this world need to remember and realize that influenced by technologies again and again like in 2010 at the past until this era 2020, will have a big impact, such a bad impact to our social and culture for all of us. For example, communication culture become fully using gadgets especially smartphones nowadays, at the beginning, the human usually communicate each other through meet the people directly at the venue. Moreover, our social experiences also will become more decreasing and it will be have a bad impact to our life like we can get a nickname as a autism person because of the addiction to their smartphones who they need, become more introvert and also difficult to express our feelings or it has communication problem for human life at the future.

So, according to me, it is better for us to concern more about balancing among devices usage with our social life, so that all of us can be a human or social beings that should it be in this world.

Fauzi Ahmad (1401164633) – MB-40-INT-2