Faculty Publications

Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736

Publications by NITK Faculty

Browse

Subject: search.filters.subject.Crowdsourcing

Search Results

Now showing 1 - 5 of 5
  • No Thumbnail Available
    Item
    Project Jagriti: Crowdsourced child abuse reporting
    (Institute of Electrical and Electronics Engineers Inc., 2014) Dhruv Chand, M.; Sankaranarayanan, S.; Sharma, C.
    Child abuse and its myriad forms often go undetected due to the geographically distributed and widespread nature of the crime. The process of reporting is also long and is often used as an excuse to allow the proliferation of these activities. To prevent the crime from going unpunished, this paper introduces a browser based web application and a mobile application called Project Jagriti that uses the power of Crowdsourcing to ensure justice for the child victims. All reports of child abuse filed using the platform are forwarded to the Child Welfare Committee (CWC); a body constituted by the Government of India to oversee child welfare and expedite the process of recovery and rehabilitation of the victims. The platform also provides anonymity for encouraging users. © 2014 IEEE.
  • No Thumbnail Available
    Item
    IntelliSearch: A search engine based on Big Data analytics integrated with crowdsourcing and category-based search
    (Institute of Electrical and Electronics Engineers Inc., 2015) Lakhani, A.; Gupta, A.; Chandrasekaran, K.
    Big Data is the technology that has changed the world. Its powerful abilities to process the data and generate the valuable data out of that has challenged the saying wisdom can be only possessed by those who have souls. Though the big data analytics is quite successful in mining the value out of the large pool of data but Big Data alone is not enough in case of web-analytics. The existing search engines lack the category based search feature and a standard ranking system for website. Crowdsourcing by involving active online community on internet is changing the shape of web applications by refining the data and improving the recommendations for the products. The paper discusses about the search engines, web-analytics toolbars and crowdsourcing to improve the web-analytics. The paper also discusses how integration of crowdsourcing with Big Data Analytics can result in 'IntelliSearch', a robust and reliable search engine. © 2015 IEEE.
  • No Thumbnail Available
    Item
    Investigating the "wisdom of crowds" at scale
    (Association for Computing Machinery, Inc acmhelp@acm.org, 2015) Mysore, A.S.; Yaligar, V.S.; Ibarra, I.A.; Simoiu, C.; Goel, S.; Arvind, R.; Sumanth, C.; Srikantan, A.; Bhargav, H.S.; Pahadia, M.; Dobhal, T.; Ahmed, A.; Shankar, M.; Agarwal, H.; Agarwal, R.; Anirudh-Kondaveeti, S.; Arun-Gokhale, S.; Attri, A.; Chandra, A.; Chilukuri, Y.; Dharmaji, S.; Garg, D.; Gupta, N.; Gupta, P.; Jacob, G.M.; Jain, S.; Joshi, S.; Khajuria, T.; Khillan, S.; Konam, S.; Kumar-Kolla, P.; Loomba, S.; Madan, R.; Maharaja, A.; Mathur, V.; Munshi, B.; Nawazish, M.; Neehar-Kurukunda, V.; Nirmal-Gavarraju, V.; Parashar, S.; Parikh, H.; Paritala, A.; Patil, A.; Phatak, R.; Pradhan, M.; Ravichander, A.; Sangeeth, K.; Sankaranarayanan, S.; Sehgal, V.; Sheshan, A.; Shibiraj, S.; Singh, A.; Singh, A.; Sinha, P.; Soni, P.; Thomas, B.; Tuteja, L.; Varma-Dattada, K.; Venkataraman, S.; Verma, P.; Yelurwar, I.
    In a variety of problem domains, it has been observed that the aggregate opinions of groups are often more accurate than those of the constituent individuals, a phenomenon that has been termed the "wisdom of the crowd." Yet, perhaps surprisingly, there is still little consensus on how generally the phenomenon holds, how best to aggregate crowd judgements, and how social influence affects estimates. We investigate these questions by taking a meta wisdom of crowds approach. With a distributed team of over 100 student researchers across 17 institutions in the United States and India, we develop a large-scale online experiment to systematically study the wisdom of crowds effect for 1,000 different tasks in 50 subject domains. These tasks involve various types of knowledge (e.g., explicit knowledge, tacit knowledge, and prediction), question formats (e.g., multiple choice and point estimation), and inputs (e.g., text, audio, and video). To examine the effect of social influence, participants are randomly assigned to one of three different experiment conditions in which they see varying degrees of information on the responses of others. In this ongoing project, we are now preparing to recruit participants via Amazon's Mechanical Turk.
  • No Thumbnail Available
    Item
    Project spear: Reporting human trafficking using crowdsourcing
    (Institute of Electrical and Electronics Engineers Inc., 2017) Roshan, S.; Vinay Kumar, S.; Kumar, M.
    Human trafficking is a severe crime which is prevailing in the society. It is hard to track and report incidents of human trafficking to the concerned authorities, due to the complex nature of this crime. This paper introduces a crowdsourcing approach to report incidents of human trafficking, using a mobile application. Crowdsourcing is the practice of obtaining information from a large number of people. Information about human trafficking incidents reported using this mobile application is forwarded to the concerned authorities of the country where the crime has been reported. A user can also upload crime scene photos and provide details of the crime location using Global Positioning System. The mobile application introduced in this paper currently focuses on top ten countries which have the highest rates of human trafficking in the world, while very basic support for the rest of the countries. Since the process of reporting human trafficking incidents to the authorities can be complex, time consuming and dangerous, the mobile application allows users to stay anonymous. The aim of this mobile application is to create huge impact in the fight against human trafficking, by using the collective power of the crowd to report incidents of human trafficking. Also, a section of the mobile application is dedicated to educating the user about basic knowledge of human trafficking, its types and measures taken by various governments to fight against it. © 2017 IEEE.
  • No Thumbnail Available
    Item
    A holistic approach to influence maximization in social networks: STORIE
    (Elsevier Ltd, 2018) Sumith, N.; Annappa, B.; Bhattacharya, S.
    Crowd sourcing techniques are used in social networks to propagate information at a faster pace through campaigns. One of the challenges of crowd sourcing system is to recruit right users to be a part of successful campaigns. Fetching this right group of people, who influence a vast population to adopt information, is termed as influence maximization. Concerns of scalability and effectiveness need an effective and a viable solution. This paper proposes the solution in three stages. At the first stage, the large social network is pruned based on the nodal properties to make the solution scalable. At the second stage, Outdegree Rank (OR), is proposed and at the third stage, Influence Estimation (IE) approach estimates user influence. This work amalgamates aspects of structure, heuristic and user influence, to form STORIE. The proposed approach is compared to standard heuristics, on various experimental setups such as RNNDp, RNUDp and TVM. The spread of information is observed for HEP, PHY, Twitter, Infectious and YouTube data, under Independent Cascade model and STORIE gives optimal results, with an increase up to 50%. Although the paper discusses influence maximization, the proposed approach is also applicable to understand the spread of epidemics, computer virus, and rumor spreading in the real world and can also be extended to detect anomalies in web and social networks. © 2017 Elsevier B.V.