loading page

Developing better Civic Services through Crowdsourcing: The Twitter Case Study
  • +3
  • Srushti Wadekar ,
  • Kunal Thapar ,
  • Komal Barge ,
  • Rahul Singh ,
  • Devanshu Mishra ,
  • Sabah Mohammed
Srushti Wadekar
Lakehead University

Corresponding Author:[email protected]

Author Profile
Kunal Thapar
Author Profile
Komal Barge
Author Profile
Rahul Singh
Author Profile
Devanshu Mishra
Author Profile
Sabah Mohammed
Author Profile

Abstract

Civic technology is a fast-developing segment that holds huge potential for a new generation of startups. A recent survey report on civic technology noted that the sector saw $430 million in investment in just the last two years. It’s not just a new market ripe with opportunity it’s crucial to our democracy. Crowdsourcing has proven to be an effective supplementary mechanism for public engagement in city government in order to use mutual knowledge in online communities to address such issues as a means of engaging people in urban design. Government needs new alternatives – alternatives of modern, superior tools and services that are offered at reasonable rates. An effective and easy-to-use civic technology platform enables wide participation. Response to, and a ‘conversation’ with, the users is very crucial for engagement, as is a feeling of being part of a society. These findings can contribute to the future design of civic technology platforms. In this research, we are trying to introduce a crowdsourcing platform, which will be helpful to people who are facing problems in their everyday practice because of the government services. This platform will gather the information from the trending twitter tweets for last month or so and try to identify which challenges public is confronting. Twitter for crowdsourcing as it is a simple social platform for questions and for the people who see the tweet to get an instant answer. These problems will be analyzed based on their significance which then will be made open to public for its solutions. The findings demonstrate how crowdsourcing tends to boost community engagement, enhances citizens ‘ views of their town and thus tends us find ways to enhance the city’s competitiveness, which faces some serious problems. Using of topic modeling with Latent Dirichlet Allocation (LDA) algorithm helped get categorized civic technology topics which was then validated by simple classification algorithm. While working on this research, we encountered some issues regarding to the tools that were available which we have discussed in the ‘Counter arguments’ section.