from transformers import pipeline
import streamlit as st
import pandas as pd
from PIL import Image
import os

# title
st.title('Combatting Climate Change Misinformation with Transformers')

# section 1: the context, problem; how to address
st.markdown("### The Problem 🤔")
st.markdown("")


# section 2: what is misinformation? how is it combatted now? how successful is this?
st.markdown("### More about Misinformation")

st.markdown("What is misinformation? How does it spread?")
st.markdown("* **Misinformation** can be defined as “false or inaccurate information, especially that which is deliberately intended to deceive.”")
st.markdown("* It can exist in different domains, and each domain has different creators and distributors of misinformation.") 
st.markdown("* Misinfofrmation regarding climate change is often funded by conservative foundations or large energy industries such as gas, coal, and oil. (1)")

misinfo_flowchart = Image.open('images/misinfo_chart.jpeg')
st.image(misinfo_flowchart, caption='The misinformation flowchart. (1)')

st.markdown("**Why does this matter?** Through echo chambers, polarization, and feedback loops, misinformation can spread from these large organizes to the public, thus arming the public with pursausive information designed to create scepticism around and/or denial of climate change, its urgency, and climate change scientists. This is especially problematic in democratic societies, where the public, to some extent, influences governmental policy decisions (brookings). Existing research suggests that misinformation directly contributes to public support of political inaction and active stalling or rejection of pro- climate change policies (1).")

st.markdown("How is climate change misinformation combatted now? Below are a few of the ways according to the Brookings Institute:")
st.markdownd("1. Asking news sources to call out misinformation")
st.markdownd("2. Teaching and encouraging media literacy among the public (how to detect fake news, critical evaluation of information provided, etc.")
st.markdown("2. Government ")
st.markdown("3. Fact-checking")
st.markdown("4. Social media platform investment in algorithmic detection of fake news")

st.markdown("However, many of the proposed solutions above require adoption of behaviors. This is difficult to acheive, particularly among news organizations and social media platforms which receive monetary benefits from misinformation in the form of ad revenue from cite usage and viewership.")

# section 3: how can transformers help?
# fever dataset
# entailment/contradiction/neutral adoption to support/refute/n.e.i.
# extention to climate

# section 4: The process
# this is the pipeline in my notes (u are here highlight)

# section 5: my work

# section 6: analysis

# section 7: conclusion

# references

st.markdown("## References")
st.markdown("1. https://www.carbonbrief.org/guest-post-how-climate-change-misinformation-spreads-online")