– by ORKASH Labs, Copyright: ORKASH Services Pvt Ltd

This blog post applies the concepts of game theory to Left Wing Extremism (Naxalism) in India. Game theory has gained importance in recent past in the study of unconventional conflicts. It is a tool for framing and analysing scenarios of strategic importance. The business world uses the principles of game theory to analyse and make competitive sense of strengths and weaknesses of the players involved for optimal decision making with respect to competetion, negotations and pricing strategies.  Corporations have been using this concept to model the mergers & acqusitions, price wars, trade union negotiations, divisional relationships, market dynamics, strikes, product launches etc. in order to make informed decisions and strategic moves.

A ‘Game’ derives its uniqueness from its rules and the way it is being played, be it a price war between two competitors or an unconventional conflict between the State and the insurgents.

To that end, extensive form of modelling has been used in this post to understand the dynamics and arrive at an equilibrium point for the left wing insurgency.

Political Angle – Arriving at Nash Equilibrium

It is understood that a politician will win an election if he aligns himself to the majority aspirations and brings about good governance. In LWE affected regions, the consensus among a proportion of the people is of an anti-State nature, with a belief that the Maoists would some day be instrumental in bringing prosperity to them. Confronted with such a situation, the plausible alternatives available to the politician in order to maximize their chances for wining the election are:

Naxal Political Payoff3

1. He/she aligns to the majority aspirations and therefore supports the Maoists/Naxals, either directly or indirectly (given that Maoism ideology has a large vote bank in the form of an existing support base), or

2. Over the long term, he undertakes developmental initiatives and works for the upliftment of the people to create a genuine support base amongst the masses. (For this to happen the politician has to compete against the support base of the Maoists/Naxals)

In the first scenario, the politician will likely reap the benefits of political allegiance immediately. In the second premise, the process is long-drawn and requires a commitment to the community. The politician has to, through his continuous efforts of bettering their lives, win over the people of the community in the LWE affected region. It is apparent that the first scenario offers the quickest results with the least efforts – the best and more efficient outcome for a politician solely interested in electoral victory.

Now, assuming that two major politicians contest an election, the outcome can be predicted by modeling the situation through the Game Theory. If both politician A and B don’t align with extremists and instead undertake initiatives and set good examples of governance to generate a genuine support base amongst the masses, then either may win the election. They have equal chances. However, it is promoting prosperity and development over the long term and is better for society as a whole. Thus, they both get a positive payoff each, from this situation, and the total of their payoffs is the maximum in this scenario – signifying the Best Possible Outcome for society as a whole. We depict this with the payoffs “A:8, B:8”.

Alternatively, if one politician aligns with the extremists while the other doesn’t (A aligns B doesn’t OR B aligns A doesn’t) then the politician who aligns with them, will win the election in this short run. This is the maximum possible payoff a politician can get as he definitely wins the election, and a better option for the individual than the earlier one (A:8, B:*) described above. The politician who does not align with the extremists is sure to lose the election. Thus, he gets the lowest possible payoff, in this scenario. We depict these payoffs as below:

If A aligns and B doesn’t – A:10, B:0

If B aligns and A doesn’t – A:0, B:10

As we can see, neither of these scenarios are best for society as a whole.

The last scenario we must look at is if both politicians decide to align with the extremists. In this case again both politicians have equal chances of winning the election. However, the important point to note is that this scenario does not lead to prosperity and development in that society. Thus the total of the payoffs of both politicians in such a situation would be less than that in the Best Possible Outcome case. We call this the ‘No Regrets Option’ since neither politician can feel regret for not having played to the interest of the majority to attempt to win. We depict this by the payoffs A:5, B:5.

Now, to predict what is likely to happen we must compare these scenarios and look at what decisions the politicians are likely to make.

In India, the primary goal is election victory, while good governance and development initiatives are unfortunately secondary goals. A major driver that creates this situation is that cast and community act as a dominant force in vote banks alignments, and the divison in vote banks resulting from three to four way election contests (two national parties and one or two regional parties being in the electoral fray in most constituencies). As a consequence governance based politics has increasingly emerges as  a lower priority. Electoral victory – a short term goal, becomes the priority, forcing the political system to align with the supporters of predominant ideology that can add to the vote banks – here, LWE.

The same is depicted in terms of the payoffs of each politician in different scenarios. No matter what Politician B does, A gets a higher payoff by aligning with extremists (If B aligns – 5>0 for A, If B does not align – 10>8 for A; so A will always choose to align). The same is true vice versa that no matter what A does, B gets a higher payoff by aligning with the extremists (If A aligns – 5>0 for B, If A does not align – 10>8 for B; so B will always choose to align). Thus, with both parties interested in maximizing their own well being, they both come to the scenario where both align with the extremists. This is the ‘No Regrets Option’ and is the Nash Equilibrium of this game.

This is why we see the political system attempting to align with the supporters of the predominant ideology of a region, so that it can add to their vote banks.

Operational Angle – Playing the Game – Changing the Rules from Sequential to One time

Politicians are the key players in the Game being played by the State (the counter insugent) and the anti-State extremists (the insurgent). This has emerged as a sequential game – with one party winning at the times when the momentary strength of the other party is weakened. Each party may take turns in winning the game (or temporarily emerging as the dominat player) since both believe that they would be the ultimate winner they continue to play numerous cycles of this sequential game. However, as a result the sequential game is a long-drawn-out and process which would likely hurt resources – both human and financial. Changing the way the game is being played, from sequential play (repetitive game of strike and counter strike) to a one-time game would probably yield more results. Thus the ‘surge operations’ in Iraq and the Greyhounds’ counter insurgency operations in Andhra Pradesh do prove a point here. Insurgency affected regions can be  generally saturated with large number of troops for area domination and population/territory denial to insurgents to bring about a situation conducive for better governance, and  while at the same time relatively smaller numbers of special forces are used in ‘strike role’ to cause attrition on the insurgents.

However, it is to be noted that tactical operations are only a means to achieve a safe environment that facilitates the restoration of the functioning of the civil administrative machinery. The surge operations need to immediately be followed by developmental programs and the creation of employment opportunities for the local populace which would bring about economic prosperity in the region and hinder any possible future extremist infusion and propogation of extremist ideologies.

In a seprate study we have calculated the quantum of resources and budgets needed (including the force levels for the counter-insurgency grid in LWE affected districts), and the capacity building and timelines that it would entail. Suffice here is to say that this would require a minimum of five year plan to just create the required resources and capcity building, and that the resources needed are large scale.

Winning the Game – Creation of a Counter-Narrative for Changing the ‘RULES of the GAME’

Owing to the current nature of law and order management in the Indian state being pre-dominantly an incident response system, the administrative machinery and law enforcement agencies typically focus more on the zones affected by violent forms of extremism.  While certainly effective to some extent, this may not be the most appropriate manner in which to eliminate the extremist movement in its entirety. In order to avoid a possible revival of the movement, the support bases need to be dismantled, as these will otherwise remain fertile grounds for germination of the underlying protest movement of the insurgency.

A community welfare based approach, especially in the peripheral zones, counters the predominant one that has been propounded by the extremists in LWE affected regions – that of State apathy and indifference. The creation, adoption and implementation of a   counter narrative in the affected and surrounding areas would be best experienced through governmental initiatives that facilitate economic prosperity and development.

Case of Northern Ireland

The outside-in devlopmental approach tends to change the Rules of the Sequential Game. It invades, weakens and breaks the support base for the extremist movement, destabilising their hold on the population. It will encourage the groups within the local communities to gradually align themselves and their resources with economic growth and development, which in turn assists the State in its counterinsurgency operations and in quelling any future onset of extremism in the area.

The British counterinsurgency experience in the Northern Ireland insurgency (as also the Greyhounds’ example in Andhra Pradesh state) is a worthy example in the study of the effectiveness of adopting a counter narrative approach to defeat the extremist movement. Through a revamp of their operational tactics from a full-fledged military onslaught to an inclusive community based approach, United Kingdom achieved greater success in margenalising the Northern Ireland secessionist movement propounded by the Provisional Irish Republic Army (IRA).


The tackling of LWE mandates a multifarious approach, focussing on development and security related interventions. The Politicain’s role remains the key. It is the Politician that can set the agenda for the governance and developmental angle to be the pre-dominant form of counter insurgency. This would need to delve into a host of forces at play (in the Game), inter alia, unemployment, poverty, land acquisition, forced displacement, distress migration, propaganda etc. Security related intervention will encompass police organisational structures, equipment, specialised knowledge of terrain, intelligence and a host of other measures for community oriented policing. In pursuing these twin approaches, we need to change the underlying drivers of the insurgency, i.e the Rules of the Game; use of game theory based modeling and maangment can shed light on underlying dynamics and sharpen the decisions, which can be a game changer in tackling LWE.


– by ORKASH Labs, Copyright: ORKASH Services Pvt Ltd

Owing to its unique geo- climatic conditions, India’s has high vulnerabilities posed by national disasters such as floods, droughts, cyclones, earthquakes and landslides. According to a Ministry of Home Affairs report, about 60 % of the landmass in India is prone to earthquakes, 12 % is prone to floods; about 8% of the total area is prone to cyclones.

Large scale disasters typically warrant two stages of response. An initial stage of information collation which enables emergence of an accurate picture, on the scale and geographic spread of the disaster. Thereafter, the stage of critical co-ordination between various state/private agencies, to provide rescue and relief.  Building blocks for the needed technology architecture is depicted in the picture below.

Disaster Management

Overcoming Opaqueness

Studies have shown that in most disasters a bulk of relief material and response capabilities invariably reside within or near the disaster zone, however, invariably reaches the victims with a time lag. Reason is that the opaqueness induced by  disaster is overwhelming, almost like the ‘Fog of War’ experienced during intense military operations. Lots of information and data exists but is unearthed only with time, by which time an earthquake ( for example)  has resulted in large scale fires and then may easily mutate into an epidemic due to shortage of clean drinking water.  Break down of law and order and attendant crimes may further delay the emergence of an accurate assessment of the disaster.

Hence, given the certainty in paucity of accurate information post disaster, the rapid creation of robust communication grids, and command and control network remains the existential challenge post a disaster. Core of such a structure needs to be an integrated net centric platform for operations planning, sourcing collective intelligence/ data, contingency planning, managing the deployment and redeployment of rescue, relief and rehabilitation, to enable a faster and efficient response to disasters.

In this context, Social Media is a versatile mean for information exchange.  Take the case of Uttarakhand floods. Many Facebook pages  became a crucial source of information. Even Twitter proved to be pretty helpful as the hashtags like #UttarakhandHelp were on the top of the trending topic list. It is also estimated that Rs 18 Crore was collected through online medium towards Prime Minister’s relief fund for Uttarakhand disaster relief, based on efforts over social media.

Most importantly, social media creates an adhoc community of ‘first responders’ who initiate and spread information and awareness, that mitigates loss of life and property. Their response is not restricted by knowledge of distress frequencies on HF /VHF or by government telephone/fax numbers.  An instant “ Stranded at Balaipur in front of State Bank building.Water gushing. Grim chances”, is enough for any twitter follower or FB friend to get into the rescue act or reach out to emergency services.

Situational Awareness

During the Thailand floods of 2011, social media had surpassed every other means of communication as a source of information. The floods were perhaps the country’s worst disasters, wherein flooding which commenced in July, lasted until December. Over 13 million people were impacted, with more than 800 deaths, with an estimate of $45 billion in terms of economic damage. As per the study titled ‘Role of Twitter during a natural disaster: Case study of 2011 Thai Flood’ , the tweets of Thai flood were classified into 5 categories:

  • Situational Announcements/ Alerts: Tweets about up-to-date situational and location-based information related to the flood such as water levels, traffic conditions and road conditions in certain areas
  • Support Announcements: Tweets about free parking availability, free emergency survival kits distribution and free consulting services for home repair, etc.
  • Requests for Assistance: Tweets requesting rescue and any types of aid; such as food, water, medical supplies, volunteers or transportation.
  • Requests for Information: Tweets including general inquiries related to the flood and flood relief such as inquiries for telephone numbers of relevant authorities, regarding the current situation in specific locations and about flood damage compensation.
  • Other: Tweets including all other messages, such as comments, complaints and opinions.

Orkash Technology

Snapshot of ORKASH Technology

Indeed, social media is rapidly evolving due to collaboration between technology and human behaviour. Virtual associations, information sharing and grass-roots rendezvous are empowering individuals during disasters, aiding rescue and relief in an unexpected manner.

Hurricane Sandy which struck the east coast of US in end October 2012, was one of the most voilent natural disasters to strike the North American continent.  Prior and during this mega Hurricane, nicknamed “Superstorm Sandy” , Twitter and Facebook were used extensively by individuals, agencies and utility companies,  to relay information, share evacuation advisories and provide updates on the storm.

Mobilising Public Resources

Even before Hurricane Sandy, New York city’s social media presence attracted 3 million followers across more than 300 city accounts on Facebook, Twitter, Tumblr etc. In addition to managing NYC.gov, the city maintains numerous channels, including Facebook pages, Flickr, Google+, Tumblr, Twitter (in both English and Spanish) and YouTube. Right through the response and recovery phases of Sandy, these platforms provided the city with the means to share information in various formats, thus proving that henceforth social media would be a crucial cog in any disaster management initiative.

Inevitably, social media also became a source for rumours. Information was verified and rumours were dispelled via a variety of tools. As a case in point, when false reports and images began circulating of New York Stock Exchange being under three feet of water, first responder agencies such as the New York City Fire Department posted messages on Twitter and other social media sites to correct misinformation.

Hurricane Sandy

As per data derived from the website www.emergencymgmt.com, the Red Cross pulled more than 2 million posts for review during Hurricane Sandy, choosing specific keyword searches relevant to Red Cross services, such as shelter and emotional support. Thirty-one digital volunteers responded to 2,386 of the reviewed posts. About 229 posts were sent to mass care teams, and 88 resulted in a change in action on ground operations.

Apps and Open Sourced Applications

The American Red Cross also offered a Hurricane App for both iPhone and Android device users to assist in individual recovery.

In fact, Apps are open sourced solutions are being tailor made for disaster management solutions. On the fully interactive Google map, geographical information related to the flooding submitted by official sources and users is aggregated in location pinpoints. During the Uttarakhand floods, Google launched a ‘Person finder’, a portal, where people could type the name of the missing person and through its immense database, Google did the matching and threw up co-relating results.

Without doubt, the challenges confronting Disaster Management in India can get a fillip with use of technology. However, many of the repetitive shortcomings experienced have been linked to organisational structure and multi agency coordination. Take the hypothetical case of a localised earthquake. Chances are that part of cellular network will survive the disaster and harnessing it in the immediate aftermath of the disaster will remain crucial.  However, mobile telecom towers can always be inducted from neighbouring regions not impacted by the disaster. For this action to take place in an expeditious manner, database/ templates of mobile infrastructure would need to be available on a Command and Control portal. Similarly, the locations of hospitals/nursing homes, including their stock of emergency medicines, can be part of the database.

ORKASH’s Integrated Disaster Management and Command & Control Solution has a Social Media Intelligence Module that greatly improves the efficiency of crises management. The solution encompasses Social Media monitoring and mining to improve the situational awareness of crisis managers and by facilitating the bidirectional communication between the public and the emergency managers.

Use of technology allows the processing of large amounts of data, therefore enabling us to collect unbiased conversations from social media (Twitter, Facebook), broadcast media (radio, TV), mobile technologies and citizens directly. In addition, the exchange of information between citizens and emergency managers, or the facilitation of communication between citizens using the know-how gathered, will allow for a timely and effective actuation of people on site. This could be for purposes like additional data collection, organizing help or simply asking people to stay away from a problem area. Coincidentally, the introduction of new structured communication channels takes load off the traditional command & control centre, thereby reducing overload situations during crises. It also helps various government and non-government agencies involved in the disaster response effort to create rapid and flexible channels of communications and information exchange using Social Media networks.

This solution innovates in technological, sociological, ethical and operational aspects and validates its findings by conducting field exercises with emergency management organizations to leverage the increasingly significant role of new communication media in crisis and disaster management and define guidelines and solutions to encourage and valorise the communication between police/law enforcement/first responders and the public, using social media.

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– by ORKASH Labs, Copyright: ORKASH Services Pvt Ltd

Social media has become a catalyst for civil mass movements and social unrest across the world. This includes upheaval in Tunisia and Egypt, Iranian election protests, disturbances to law and order across India in response to Delhi gang rape case in December 2012, Anna Hazare anti-corruption movement in India, the 2011 riots in London, etc. The list goes on.

This proliferation of Social media, especially through the ubiquitous mobile phone, coupled with bursting population in urban areas, poses an unprecedented challenge as well as an opportunity for Law Enforcement agencies across the world. Social media provides a powerful communication platform for organising protest and civil unrest; but on the other hand it can give government and police agencies with the means for real time intelligence, and, more importantly, the ability to intimately understand the ‘pulse and mood’ of the people; for example their reason for discontent and the underlying societal stress points of a community group. Social media also has a tremendous potential for creating accountability and governance transparency through ‘virtual’ non-intrusive partnerships between the police and the local communities.

Public Partnership for Policing – Boston Bombing

Take the case of the recent Boston Marathon terror bombing. Unlike the last time the continental United States was attacked, (11 Sep 2001, when social media sites like Facebook and Twitter were not even conceptualized), this time in Boston the social media platforms became a shared public repository for video and photos from the scene, with the people at large, as a result, becoming an active participant in the search for the terror perpetrators.

Consequently, the two plotters became the “target” for the social media communities, and not just a headline in the media. The FBI then decided to release photos of the alternative key suspects that they had identified. It is highly probable that FBI would have held on to the photos a bit longer and not actively engaged the public in the search, if the online narrative on social media was not running so fast and furious. Preemptive release of their photos by the FBI, and due pressure by the demand for instant information in the social media world, forced the terror suspects to move earlier than they had intended, forcing them into a series of mistakes.

In addition, during the three-day lockdown of Boston, over 80,000 people turned to smart phone apps, the Internet, and any available radio listening device to follow along with the Boston Police scanner. Consequently, the most trending hash tag on Twitter was #BostonPoliceScanner. All this resulted in an unparalleled public-police collaboration, as the Police advised most Bostonians to stay indoors, the social media became the medium for the resident communities to coordinate the city-wide lockdown as police went about ‘hunting’ the terror suspects. Residential communities followed instructions of the police and also spread the word on social media. Thus what emerged was a Public Partnership for Policing, underpinned on voluntary and community ownership.

Predictive Intelligence – London Riots

For the Law enforcement agencies, social media analytics can quickly pick up intelligence on high-risk behavior. This was demonstrated during London riots of 2011. After an initial lag, the London Metropolitan Police reportedly used social media data to predict occurrence of riots in specific localities. The algorithm was based on following logic flow. Geographic clusters of mobile phones were identified on a real time basis, using location data provided by Telecom operators. The mobile concentration were indicative of a mob or a crowd assembling at specific location. The cluster was then analyzed to rule out occurrences like a traffic jam or a large party/social gathering which could also result in concentration of mobiles in an area. Thereafter, the inter communication pattern between the mobiles in the concentrated area was studied. For example, within a traffic jam the inter- communication would be very low but high in case of a mob with malicious intent where the mob-leaders were found using twitter to organize the mob.

Once such a trend was identified, the ‘sentiment analysis’ of tweets within this mobile phone cluster helped ascertain use of ‘emotionally enraged or incensed’ language, and determine the ring leaders through identification of key nodes in the communication patterns of the identified mobile phone cluster. Thus, such pattern analysis gave an early warning of potential mob violence and the real-time state of the crowd’s/mob’s state of group psychology. Counter actions in such a scenario can include jamming of mobile phones of key influencers and pre-emptive arrests of the mob leaders, and more informed redeployment of Police resources for pre-emptive incident response.

Nirbhaya Rape Protests, Delhi

The unprecedented protests and social upheaval following the Nirbhaya gang rape in New Delhi, on 16 December 2012, was triggered in a large measure due to social media. As a representative example, Sikha (name changed), 19 years, was at Jantar Mantar monument on December 25 protesting against Nirbhaya’s brutal rape when Delhi Police swooped down, rounded her up along with other agitators and took them to the Parliament Street police station. Sikha fired tweet after tweet even as she was bundled into a police van. She went on broadcasting to the world all that was happening around her. “Illegally being held here at Parliament St Police Station Delhi w/ 15 other women. Terrified, pls RT,” she tweeted. It worked. In a flash, more than 1,700 people retweeted her SOS tweet. Social media analytics indicate that the message reached over two hundred thousand people and resulted in a sympathy wave leading to even greater protestors’ crowds.

As the protests escalated across the country, water cannons, baton charges, and tear gas were quick to be deployed on the streets, especially in New Delhi. In hindsight, pre-emptive intelligence picked up from social media could have helped mitigate or prevent such a volatile outcome. Most importantly, the sentiments and opinionsbeing expressed on social media could have provided the police with insights intoemotional and psychological stress points driving the protestors – the most importantfactor that the police agencies need to know to prevent escalation of the violence and to de-escalate such a situation.

Orkash Technology

The above screenshot of ORKASH Socia Media Intelligence Platform identifies  the geographic clusters of tweets when Nirbhaya rape case protests were in progress in Delhi in December 12. Further, this technology enables detailed automated analysis of the sentiments and behavioral aspects of the tweet contents, which indicated build up of resentment and fury in the protesting crowds, giving timely indication of the transformation of some segments of the crowd into a mob, and their psychological state.

This kind of analytics and data mining of social media feeds, however, requires a complex architiecture of unstructured-data mining tools, hardware and services, (and policy controls) in the form of a Social Media Intelligence platform because of the large amounts of data to be analysed in real time. This also needs a Data Sciences approach to sentiment and behavioral analysis of the comments and traffic patterns, and temporal analysis about anticipated events. None of these are easy or readily available technologies in the current state of things!

Community Engagement for Law and Order

A recent research report has established that nearly 45% of the 100 million plus Indian web users, most of them from urban areas, connect on social media to discuss politics and social issues. Only Arab countries scored higher than India on this account. Thus, any and every Indian state agency that is a stakeholder in the Law and Order domain will need to build up expertise on analyzing social media inputs, for this is an excellent platform for listening to community and public voices. As in other countries, it is a fact that urban India resides in high density pockets. These are invariably social or ethnic clusters in large cities, underpinned further by religious/regional/linguistic/community identities.

The young population in lower-income pockets of large cities are often defined by squalor and depravity of ‘urban ghettos’, and are forced to reconcile their dreams with their economic and social reality, which often makes them susceptible to crime, drugs, radicalization and even terrorism. The RWA’s (Resident Welfare Associations) or local community leaders in such pockets are an ideal channel for the Police to tap into, and grasp, the human angle context to crime and its prevention dynamics. However, such community policing is through traditional physical interface due to perceptions of intrusion or trust. In such situations, social media accords an ideal forum for the Police to engage with the ‘Mohalla’ or local community populace without an ‘intrusive’ forward presence. This has been done fairly successfully by the Police in UK in its policing programs for vulnerable community groups.

Various police forces across the world have set up a social media monitoring facilities. These “Social Media Labs” monitor the likes of Facebook, Twitter, Google+ and other prominent social media platforms to measure changes in mass moods and track matters concerning public law and order. Police teams across the globe are also keeping a vigil on widely discussed and trending topics, in order to tie social media and criminality together. The NYPD (New York Police Department) has a program to mine social media for information about “troublesome house parties, gang showdowns and other potential mayhem”, and so has Mumbai Police recently created a Social Media lab.

Future Challenges & Opportunities

The perennial challenge for any Police department is that the amount of data covered by social media posts, updates, and tweets, will be next to impossible to monitor using traditional technology. This requires large scale infrastructure and Big Data scale of mining and analytics for textual unstructured data alongwith automated cognitive and temporal analysis. ORKASH (www.orkash.com), alongwith the likes of IBM (the Watson project), is amongst a handful of companies worldwide with the technology to do so. Of course, the inevitable dilemma surrounds the issue of privacy. Without a warrant, what information should law enforcement be able to access? Where is the line to be drawn insofar as digital intrusion is concerned? In potentially life-threatening situations, should social networking sites provide information and personal details? Though such questions may remain unanswered in the near future, the peril would be greater if they remain unasked.

Police forces have regularly received a “shot fired” message via Twitter and suspicious person reports on Facebook. Additionally, in large scale disasters scenarios, e.g. earthquakes or large terror strike, Social Media can be used for seeking and arriving at ‘situational awareness’ and optimising the incident response efforts of emergency services in the rapidly changing and confusing scenario of a disaster. More about this in our next blog post.

In conclusion, in a manner similar to beat-patrols, the Police forces will need to patrol the virtual world of social media. Be it for ‘connecting’ with the people, community-police partnerships, demonstrating presence, picking up incidental information or analyzing the conversations for pre-emptive intelligence, social media accords an unprecedented opportunity.

The accompanying snapshots illustrate the Social Media Intelligence solution developed by ORKASH Labs. They can be customized for specific Policing requirements.

Assam Roits Final

This snapshot depicts network linkages generated form ORKASH’s Social Media Intelligence platform. The graph above reveals linkages between various twitter handles commenting on the Assam riots and the User IDs (blurred out) involved in spreading rumors and   provocative  content targeted at  one particular community in cities like Bangalore and Pune, which then led to exodus of people of North-eastern origin from these cities. Font size of the handle indicates its significance in terms of influence. 


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