Sunday, October 22, 2017
Engaging passionate sports fans and followers to generate revenues for companies, sponsors and tournament organizers
Millions of people from around the world play or watch sports. People often follow multiple sports, teams and individual sports personalities. For the sake of this paper, we will just focus on one sport – Tennis. There are lot of schools, colleges and sports academy around the world where tennis is being taught. The students from all these schools, coaches and working professionals around the globe follow tennis and are fans of their favorite tennis players.
There are few tennis player fan clubs on Instagram and Facebook but all are very disintegrated and none of them has enough appeal to keep fans engaged for long. Also, they are only there to give regular updates of the ongoing tournaments and match scores but nothing more than that. Also, the major tournament (Four grand slams and ATP World Tour) organizers focus merely on ticket selling but not connecting the fans. They are not able to do it because they don’t ask enough questions while selling the tickets. They have the best opportunity to sell tickets at higher price, engage more businesses in the process but are not doing it. People following specific fan in Facebook could be a quick breakthrough for companies looking for fans but still not 100% effective when it comes to engaging fans.
How can we increase the engagement of the fans and generate higher revenues for businesses out of it, creating a win-win situation?
· Create a survey questionnaire asking for:
2) Address (Home country and current address)
4) Age (10-18: Value 1, 18-25, Value 2, 26-32, Value 3, 32-40, Value 4, 40 onwards, Value 5)
5) Favorite player
6) 2nd favorite player
7) Favorite grand slam
8) Avg. No. of times tennis being watched in a month
9) Avg. No. of times tennis being played in a month
10) Social media network used (e.g. Facebook, Instagram, Both)
11) Favorite sports accessory (Cap, T-shirt, shoes etc.)
12) Last Grand Slam/ATP Tournament visited if any
13) Self- rating as a fan (Crazy =1, V. Good =2, Good = 3, Avg. = 4, So called = 5)
14) No. of meetings with other fans in a month. State the names of two other fans with whom you are connected.
15) Willingness to travel and spend time with other fans (Yes/No)
16) Profession and Role (Hierarchy)
· Roll out this survey to tennis academies, schools, universities and big grand slam events where thousands of fans purchase their tickets. Survey could also be rolled out on Social Media.
· In order to receive more number of responses of surveys and ensuring success of it, several different strategies can be used including draws, discounted tickets to tournaments, goodies, etc.
· Once we have the survey responses from around the world, we can use social network analysis for the resulting 2-mode network.
· Dichotomize the data at fan level 1 for a specific favorite player and analyze using SNA network cohesion features.
Ø SNA would be a very appropriate tool for answering the overarching question because it allows to look at:
· Sub-groups and Cliques: Looking at groups within Academy, Sports Clubs, City, Country, Age, Similar Career Interests, etc.
· Betweenness: Looking at the shortest path to reach other fans and see who can influence who
And other measures like Eigen-Vector, Factions and Degree Centrality once we focus on certain attributes.
Companies can form strategies to:
Looking at the sports value chain as mentioned below, companies can target all the four pillars of sports value chain.
· Gather group of like-minded fans, run marketing and sales campaigns of specific products, sell them sections of fan specific stadium tickets, organize celebrity meetups and group activities.
· Connect with Hotels, Tournament Sponsors, Travel & Airline companies, Official Beverage partner, Sports branding and goods companies to form a club allowing for revenue with membership fees and organize fan oriented events, creating a win-win situation.
Due to increased engagement, relationships among fans could be developed over time and it could further create more business opportunities.
Previous blog used as reference:
I am not taking 2nd module of the course
Saturday, October 21, 2017
Russian Info Ops on FB and Twitter: Correlation with Violent Crime?
Background & Premise
Russian Information Operations targeting US citizens ramped up significantly in 2015 and even more so in 2016 leading up to the November presidential election. Further, these operations have a vastly broader scope than the presidential election alone—the operations are extensive and ongoing, they seem to be largely successful (at least as evidenced by the rhetoric of Russian sources who work or have worked for such efforts, and at least in comparison to similar Russian efforts in Finland, Germany, and France), and they target US domestic religious groups, social movements, state and local governments, educational institutions, and more.
These operations are born out of a robust info ops infrastructure with close ties to Russian oligarchs and government agencies. Most operations, and the Russian agents and agencies sponsoring and orchestrating them, were created with specific political goals in mind, such as:
· Undermining the strength of US democracy and civil institutions, and eroding public faith in them,
· Weakening US reputation and credibility abroad,
· Further dividing the US population over contentious political issues,
· Increasing violent and hate-based protests (marches, secessionist movements, etc.) in the US.
For the purposes of this SNA, data will focus on these groups’ efforts to incite, whether directly or indirectly, violence in the US. Russian info ops have been linked to white supremacist protests in Charlottesville and elsewhere, violence between Black Lives Matter and police officers (on both sides), armed secessionist marches in multiple states (most notably Texas), armed protests on behalf of religious groups (such as Westboro Baptist Church), and many other protests that were of a violent nature or that could quickly have escalated into violence.
One of the chief avenues of influence through which Russian agents influence US citizens is social media. US citizens frequently do not realize they are communicating with Russian agents or are part of Russian government funded and organized groups pretending to be US grassroots groups.
“Lit Review”/Other Work in this Field
Just one example of the research being done in this space is the Hamilton 68 project, which uses a variety of analytic tools (not SNA, but complementary analytics) to examine the extent of Russian Influence Operations on Twitter (RIOT), named for Alexander Hamilton’s 68th essay of the Federalist Papers, which has to do with foreign interference in US elections. RAND has conducted extensive work on information operations, and Foreign Policy has for months been publishing multiple articles a week on Russian info ops in the US. SNA has certainly been used by both US and Russian organizations in examining this field, particularly in conjunction with SOF, though it is not open-source.
The key research question is: are Russian information operations on social media significantly increasing the level of violent crime in the US?
Scope & Data Gathering Methodology
Citizens convicted of most violent crimes in the US are listed in public state databases. The SNA will be limited to FB and Twitter groups sponsored by Russian government organizations between 2015 and 2017, and Facebook and Twitter users who 1) were public members of these Facebook groups or were following these Twitter groups with public, personal Twitter accounts, and 2) who were subsequently convicted of violent crimes. This is publicly available data—we first look up those convicted of a violent crime in the last two years in a given state, and we subsequently run through the list of names to see whether each was a member of / was following certain FB/Twitter groups.
In addition to areas of potential insight from the SNA, elaborated on below, the fundamental answer to the research question will be answered primarily by comparing rates of violent crime among individuals who were followers of Russian influence operations with overall rates of violent crime in various states. If US citizens actively following several Russian agent-operated FB and Twitter groups are 2.4x more likely to be convicted of a violent crime as citizens not actively following such groups, for instance, then there is a clear correlation between these operations and the number of violent crimes in the US.
To allow for a more manageable scope, other social media platforms will not be included (though they are certainly relevant—see “Further Analysis” below).
Further allowing for a more manageable scope, at least at the advent of the project, the SNA will focus solely on groups that are publicly known to be run by Russian agents (notably by the Russian Internet Research Agency). The project will not examine all 3000+ FB ads that were Russian-sponsored—in addition to numerical problems, it is too difficult to determine who viewed particular ads, and FB does not disclose this data publicly.
There are a number of potential flaws with the methodology. First, the influence of info ops is not limited solely to violent crimes. Second, most of those involved in extremist and/or hate-based movements in the US are not subsequently convicted of violent crimes. Third, many of those influenced by Russian operations are not actively following such groups, but are influenced by intermediaries—friends, neighbors, coworkers. Fourth, though not final, there are doubtless many FB/Twitter groups run by Russian info operatives that we are not presently aware of. We are operating from a limited pool for the purposes of this SNA. However, the analysis will still yield important insights into the research question and perhaps into the larger field of information operations.
This project leaves substantial room for further analysis that would likely provide compounding insights. In terms of initial analysis, this SNA project would be best approached 1) by first looking at FB groups, and second looking at Twitter operations; and 2) by working state-by-state through databases listing individuals convicted of violent crimes. This is publicly available information, though it varies state by state—some states, such as Texas, list all individuals convicted of “Class B Misdemeanor” crimes and above, while some state databases include individuals convicted of felonies only, etc.
For further analysis, other social media platforms could be included. The same day that FB shut down the FB group of the largest secessionist movement in Texas, for instance, which was run directly by Russian agents, the group moved to Instagram.
Additionally, the further analysis that might yield the greatest insights would be to delve deeper into the connections between the Russian influence operations and the extent to which US individuals were effectively influenced. This would address a more qualitative, equally essential part of the research question; SNA is just one important technique to get to the heart of the problem.
SNA would be especially valuable in the beginning as a means of demonstrating the magnitude of the problem both to policymakers and to the targeted, influenced citizens themselves, particularly in an increasingly “bubbled” society. Ultimately, further analysis might yield insights into the methods and processes through which the Russian info operations infrastructure works, and ways in which the US citizenship might be made more resilient to such influence—particularly where such influence leads to greater violence.
This project will create a two-mode SNA using FB and Twitter groups sponsored by Russian government agents/agencies as one mode (“node type 1,” distinguishable by color) and specific individuals who were convicted of violent crimes and who were members of or followers of these FB and Twitter groups as the second mode (“node type 2”).
In the analysis, I will examine different levels of dichotimization of how many Russian-sponsored FB/Twitter groups of which each individual was a member. If available data is sufficient, and if macros provide an effective tool to gather the data, I’d also like to code for and examine different levels of dichotimization of how active each individual was in each group (i.e. number of posts in a Facebook group, number of retweets of a Russian agent’s post, etc.). This would create an additional, valued matrix for my analysis.
Centrality measures and tie strength might prove useful for analyzing which FB/Twitter groups were most influential, and the extent of their reach. Some US citizens active on social media might, for instance, be shown to have significantly extended the reach of such groups if they show a high Betweenness between group creators and violent criminals—event organizers, for instance. There might also be a correlation between those convicted of violent crimes acting out of strong feeling towards a particular political issue, and the number of FB/Twitter groups they were influenced by (Eigenvector and Egonets are two ways of further examining this)—from this, one might argue there is evidence of “stacking” influence. Centrality measures might also provide insight into which contentious issues were most effectively manipulated into violence—whether, for instance, followers of race-focused groups were more likely to be subsequently convicted of violent crimes than followers of religion- or secession-focused groups. Many other possible insights from tie strength and various centrality measures are possible with further analysis.
Further insights would likely be gleaned from faction analysis, particularly when analyzing the overall network by region. It might be possible, for instance, that certain regions of the US were more prone to influence escalating into violence than others. With sufficient data, faction analysis might also show which Russian groups were most effective at inciting violence among US social groups.
Attributes that could be linked to specific nodes include:
Node Type 1:
· The specific government or government-contracted agency/corporation sponsoring political information operations targeting the US public.
o If publicly available data is sufficient, research might allow for two distinct attributes- one for sponsorship, in terms of funding, political endorsement/authorization, and logistical support, and another for orchestration, referring to the agents actually authoring and posting in such social media groups, pretending to be US citizens with divisive opinions, etc. (operating a level below the individual/institutional sponsors).
o Again, if publicly available information proves sufficient, these attributes might be further subdivided by the ties or types of ties that info op sponsorship institutions have to high level Russian politicians, oligarchs, and other power brokers (President Putin, members of the Politburo, billionaires). Further SNA analysis is required before these ties and types can be effectively categorized.
· Attributes corresponding with a particular US region or particular, divisive US political issue.
· For further analysis, broadening the scope: Social media groups and activity limited specifically to influencing US opinion; to influencing Russian opinion; to influencing opinion (and available information, and upsetting the veracity of available information) in other countries towards the US and/or towards Russia; and any overlap/interrelation.
Node Type 2:
· Type of violent crime of which the individual was convicted, and crucially—requiring further research and analysis—whether the crime was motivated by hatred towards specific groups of a diametrically opposed political stance. E.g. violent protests by white supremacists influenced by Russian propaganda designed specifically to promote hatred towards blacks, or towards immigrants; lone wolf attacks against police officers by citizens who were members of Russian-operated groups that promoted violence against law enforcement; etc.
· Whether the individual followed Twitter groups or Facebook groups, or both.
With the intention to understand the effects of the migration crisis on social and political climate in the Western Balkans, I spent three months in Serbia in the summer of 2017. During this time, I conducted interviews with community leaders, representatives of NGOs, government officials who have been working with the refugees and migrants since the beginning of the migration crisis, migrants and refugees in asylum and community centers, as well as the representatives of the far-right movements who have been vocal about the migration crisis. My initial findings pointed to low anti-immigration activity on the ground as most far-right movements interviewed had not defined their stance on migration related issues. Most well established nationalist parties and far-right movements and organizations avoided the migration related questions as they were still in the process of strategizing best approach to the issues that came out of the migration crisis and their political potentials and consequences.
Due to the relatively low activity of nationalist parties and far-right movements on the ground, I set out to explore online presence of the far-right and anti-immigration movements in Serbia. Growing influence of the European movements and their utilization of social media pushed me towards several well-established Facebook pages that propagated anti-immigrant sentiments and strong nationalist policies in Serbia. After establishing communications with several of the admins of the anti-immigration Facebook pages, I was introduced to an interesting network of anti-immigration activists in Serbia and Europe and the US who are closely connected with nationalist parties and movements and whose main platform is based on the idea of national rebirth. It turned out that, even though anti-immigration movement is not very active in Serbia at the moment, the idea of protection of national identity and disappointment with European Union and its “failed multiculturalism” are of great interest to Serbian far-right movements. Serbia, on the other hand, is of interest to the anti-immigration and nationalist movements in Europe and the US because it represents “fertile ground for national rebirth.” These two reasons present a strong motivation behind creation of network of Western Balkan and European and US far-right movements and the migration crisis and the issues that emerged out of it seem to be one of the main catalyzers for collaboration. Therefore, this project seeks to use social network analysis to portray and analyze a small part of a larger global network of the far-right movements that strongly reemerged as a result of anti-immigrant sentiment born out of the most recent migration crisis.
Main Research Question
What is the degree of connectedness and cooperation of anti-immigrant far-right organizations from Serbia with organizations in Europe and the US?
The goal of this research question is to obtain insights into general activity and patterns of communications between the Serbian anti-immigrant and far-right movements with similar European and US movements and nationalist parties.
The purpose of the project
In recent years, Europe has experienced a massive influx of refugees from Middle Eastern and African regions, mainly due to civil wars and economic stagnation in these areas. In Western Europe this influx peaked in 2015 when chancellor Angela Merkel decided to admit the entry of Syrian refugees stuck in South-East European countries. These developments have been accompanied by a steep rise in popularity of nationalist parties and movements across Europe and the United States. Use of social media was strongly leveraged to communicate the messages to followers and to foster a strong sense of community of movements and people fighting for a common cause. This global unification of the far-right has started affecting the nature of nationalist movements in Serbia as well. Previously concerned with exclusively Balkan oriented policies and disputes with the neighboring countries, the “new far-right” of Serbia is much more connected with European and US movements as a result of the migration crisis and the “solidarity” that the movements have started cultivating under the pretense of the need for protection of national borders and return to traditional values.
SNA has been used for a long time to analyze terrorist networks and movements, but it is yet to be fully utilized when analyzing far-right nationalist movements and parties. One of the reasons for this is that the far-right movements have not been fully recognized as a security risk in the US or in Europe up until very recently. It has been apparent from the events that have occurred recently that far-right extremism presents a serious domestic concern for countries globally as it exposes the pre-existing internal problems in developed democracies that serve well these movements as they point to the fact that many of the social problems and inequalities even in the most developed liberal democracies are yet to be addressed. Given the potential security threat posed by extremist organizations, it is important that general public as well as the governments and intelligence agencies understand how nationalist parties and far-right movements mobilize and connect both online and offline.
This project will help identify the “new right” on the rise in Serbia and its relationships with the larger network of movements from Europe and the US. Mapping out a part of this network and identifying and characterizing relationships of different movements and parties within it will allow for identification of the most connected movements, potential sources of funds, recruitment strategies, and other important characteristics of the network that can allow for better understanding of ideology and organizational structure of the nationalist subculture.
Data Collection and SNA Methodology
Data for this project will be collected on two different levels:
1. Individual Representatives - Through desk review, participant observation, and semi-structured interviews in the field, I will collect data on ties between individuals and their parties and movements. The interviews will allow me to identify and examine the theoretical assumptions about the ideological connections and exploration of individual motivations and experiences and their interpretation of the nature of relationships and connections with the European and US movements and individuals from the far-right. (Most of this data has already been collected, but some additional interviews might be conducted throughout the semester.)
2. Movement and party connections – A web crawler will collect data on the links between the movements and parties identified through field research. This data will be used for creation of digital maps of the network to show general patterns of cooperation and contestation amongst organizations on the far-right. Centrality measures will be used to identify patterns of communication and the way that network shapes the performance and influence of different movements.
This project will focus on the overall network rather than analysis of individual relationships. The two-level analysis, however, will allow for identification of actors who are at the core of the network of movements identified through field research and how these movements interact and behave.
Given the time constraints, I intent to closely examine only a small part of the network of movements in Serbia and their connections with the European and the US far-right movements and nationalist parties. Through field interviews conducted during the summer 2017, I have identified 10-15 movements and individuals associated with them and they will be the basis from which the online data will be collected to better understand their network.
Limitations and Challenges
One of the challenges that this project faces is the ever-changing nature of the movements and parties in question. A lot of individuals identified through field research belong to several movements and parties at a time and the movements themselves often change names and disguise their mission by adopting different organizational structure. Even when individuals and movements are identified and their websites are tracked, there will need to be a significant amount of manual tracking of content and continuous monitoring in case that some movements dissolve or get re-branded during the data collection period.
Friday, October 20, 2017
Evaluating and Improving Janaagraha’s civic awareness program
I will be taking the second half of the module and will be working on the WEF Project.
‘Janaagraha’ is a non- profit organization based in Bangalore, India that facilitates various programs to foster civic awareness amongst citizens. One such program is called ‘Bala Janaagraha’ in which Grade 8 students across schools enrolled in the program are taught civic awareness and citizen rights based on a curriculum set by Janaagraha. Once the school is enrolled, it’s mandatory for the Grade 8 students to study the curriculum and pass the tests. The program includes class room learning as well as projects undertaken by these students which reflect a good understanding of civic awareness.
The main objective of Bala Janaagraha is to empower the Indian youth in understanding the power of citizen rights, proper governance and a better quality of life. Every six months, the quality of the Bala Janaagraha program is evaluated based on feedback from the facilitators of the program as well as from the students across schools enrolled in the program which is conducted by surveys. The structure of the survey that’s rolled out to students is primarily built around the curriculum of the program as a test of their understanding. An effective way of measuring the impact of this program is being conducted through pre-and post-surveys (both surveys having the same questions but the pre-survey is targeted to students prior to the start of the Bala Janaagraha program and the post survey aimed at Grade 9 students who have completed the program in the previous year). The responses are then analyzed to see how effective the Bala Janaagraha program has been in educating students about civic and governance issues (measured by the number of questions answered correctly by both groups- the students who took the pre-survey and those who took the post survey).
I worked in Janaagraha over the summer and conducted a Monitoring and Evaluation of the Bala Janaagraha program across 15 schools enrolled in the program. Based on the results of the pre-and post-surveys across these 15 schools there was a significant difference in the results between the two groups. Those who had completed the Bala Janaagraha program performed better than those who hadn’t been through the program.
Given the effectiveness of the program, I’m interested in considering how Bala Janaagraha can tailor their curriculum based on the interests of the students around a broad range of issues to understand the trends around students and issues and how Bala Janaagraha can use it as a leverage to address other pressing issues of equal importance but lack considerable awareness.
Using SNA Analysis:
SNA Analysis can be used in connecting these 2 groups of students across schools by issues that resonate with them. The network would be a two- node matrix classified based on attributes and issues. The measures I would use as a part of my SNA Analysis would be degree centrality including betweeness to understand the structure of the Bala Janaagraha team- how the various students relate to their facilitators, which facilitator controls the curriculum and program across schools. I would also use factions to analyze the network based on subgroups- the subgroups being schools and if there are similarities amongst students across certain schools and whether the facilitator in charge of the schools has any affect or if there are any other factors despite the standardized curriculum across schools. I would also look at in and out degree between facilitators and the students to understand the flow of communication and among the facilitators to determine whether they are well coordinated.
The data required would be a list of Grade 8 and Grade 9 students enrolled in the program. In addition to the pre-and post-survey data, we would need an additional survey with student responses to their issue of interest, their gender, whether they have been directly or indirectly affected by the issue of their concern, have they undertaken a project that addresses any issue of their concern. We would also need a list of the facilitators in charge of running the program across schools and their attributes.
Based on the responses of the surveys, SNA will help me determine how well connected facilitators are with their students, whether there’s coordination across schools in maintaining the same standard across schools. It would also provide insight into whether the program can be better organized to help facilitators understand key issues that students are interested in and maybe undertake projects that have a deeper value to those students. It can also help identify gaps in the curriculum that don’t address issues in as much detail as it should to address those of key interest articulated by students in their surveys.