Methodology

1. Data :

Temporal case law data will be acquired from the district courts with the scope of data collection being limited across time, geography and the type of cases registered within the courts. These variables are defined below.

2. Geographical spread (States/UT’s):

3. Jurisdiction:

District Courts in the above-defined eleven States.

4. Data Source:

eCourts - https://districts.ecourts.gov.in/

5. Time Period :

27/10/2009 to 15/02/2020

6. Acts & Sections:

All cases registered under the following acts/sections:

• Section 66A, Information Technology Act 2000 - Punishment for sending offensive messages through communication service, etc.

7. Data Collection:

The data was collected using the E-courts Application Programming Interface (API). The API parameters were decided as follows:

• Conducted a manual search to identify if all cases on the website including a charge under S.66A were tagged as such on the E-courts website. The observations from the manual tests can be summarized as follows:
  • Some cases which included a charge under S.66A were tagged as under the Information Technology Act, but not as a 66A case under the section tags;
  • Some cases including a charge under S.66A were tagged as S.66a ( or another variation including a combination of components "Section" or "Sec" and "66" and "a" or "A". Visit our Challenges section to learn more about the non-standardisation of data across the E-courts data); and
  • Certain sections of the Indian Penal Code(IPC) were repeatedly invoked with a charge under S.66A.
• The main parameters were, therefore, in the first instance, cast wide to include all cases under the Information Technology Act, 2000. Considering the consistent presence of certain IPC provisions, we further cast our net to include all cases under these specific provisions of the IPC.

• The above list of cases was then manually curated based on the sections invoked in the cases. Cases involving any variation of 66A i.e. 66a, 66(a),66AC etc. were flagged positive, and the rest of the cases were filtered out. This resulted in a list of cases with 1163 variations of the Section description.

• This list was then further manually curated by reference to judgements and orders, where present, to create the final data set.
  • Cases without an order/judgement were marked negative and filtered out to avoid a false-positive result.
  • There are a number of cases with ambiguous tags which we have not been able to verify due to the lack of orders/judgements. Due to our inability to verify them these cases have currently been excluded from our final dataset.